Cure Model Regression
cureit.RdCure Model Regression
Usage
# S3 method for formula
cureit(
surv_formula,
cure_formula,
data,
conf.level = 0.95,
nboot = 100,
eps = 1e-07,
...
)
cureit(object, ...)
# S3 method for default
cureit(object, ...)Arguments
- surv_formula
formula with
Surv()on LHS and covariates on RHS.- cure_formula
formula with covariates for cure fraction on RHS
- data
data frame
- conf.level
confidence level. Default is 0.95.
- nboot
number of bootstrap samples used for inference.
- eps
convergence criterion for the EM algorithm.
- ...
passed to methods
- object
input object
See also
Other cureit() functions:
Brier_inference_bootstrap(),
broom_methods_cureit,
nomogram(),
predict.cureit()
Examples
cureit(surv_formula = Surv(ttdeath, death) ~ age + grade,
cure_formula = ~ age + grade, data = trial)
#> 0 were not able to fit
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.002616112 0.569504769 0.345883977
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.575003030 0.009813492 0.108542405
#> grade_iii, Cure model
#> 0.823899189
#>
#> $surv_formula
#> Surv(ttdeath, death) ~ age + grade
#> <environment: 0x56211567b0c0>
#>
#> $cure_formula
#> ~age + grade
#> <environment: 0x56211567b0c0>
#>
#> $data
#> # A tibble: 200 × 8
#> trt age marker stage grade response death ttdeath
#> <chr> <dbl> <dbl> <fct> <fct> <int> <dbl> <dbl>
#> 1 Drug A 23 0.16 T1 II 0 0 24
#> 2 Drug B 9 1.11 T2 I 1 0 24
#> 3 Drug A 31 0.277 T1 II 0 0 24
#> 4 Drug A NA 2.07 T3 III 1 1 17.6
#> 5 Drug A 51 2.77 T4 III 1 1 16.4
#> 6 Drug B 39 0.613 T4 I 0 1 15.6
#> 7 Drug A 37 0.354 T1 II 0 0 24
#> 8 Drug A 32 1.74 T1 I 0 1 18.4
#> 9 Drug A 31 0.144 T1 II 0 0 24
#> 10 Drug B 34 0.205 T3 I 0 1 10.5
#> # ℹ 190 more rows
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> $surv_xlevels$grade
#> [1] "I" "II" "III"
#>
#>
#> $cure_xlevels
#> $cure_xlevels$grade
#> [1] "I" "II" "III"
#>
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 7
#> term estimate std.error statistic conf.low conf.high p.value
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure mod… -0.575 0.478 -1.20 -1.51 0.362 0.229
#> 2 age, Cure model 0.00981 0.00982 0.999 -0.00944 0.0291 0.318
#> 3 grade_ii, Cure model 0.109 0.367 0.295 -0.612 0.829 0.768
#> 4 grade_iii, Cure model 0.824 0.387 2.13 0.0655 1.58 0.0332
#>
#> $tidy$df_surv
#> # A tibble: 3 × 7
#> term estimate std.error statistic conf.low conf.high p.value
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00262 0.00903 -0.290 -0.0203 0.0151 0.772
#> 2 grade_ii, Survival mo… 0.570 0.282 2.02 0.0164 1.12 0.0436
#> 3 grade_iii, Survival m… 0.346 0.223 1.55 -0.0905 0.782 0.120
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.575003 0.009813 0.108542 0.823899
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.5
#> Residual Deviance: 253.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.575003030 0.009813492 0.108542405 0.823899189
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.002616112 0.569504769 0.345883977
#>
#> $b_var
#> [1] 0.2286519015 0.0000964799 0.1350330845 0.1497399357
#>
#> $b_sd
#> [1] 0.478175597 0.009822418 0.367468481 0.386962447
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.2024935 0.9990913 0.2953788 2.1291451
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.22917240 0.31775048 0.76770451 0.03324226
#>
#> $beta_var
#> [1] 8.155501e-05 7.963690e-02 4.957568e-02
#>
#> $beta_sd
#> [1] 0.009030781 0.282200108 0.222655965
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.2896883 2.0180884 1.5534458
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.77205469 0.04358205 0.12031666
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.000000000 0.000000000 0.000000000 0.604678067 0.658063410 0.000000000
#> [7] 0.417229340 0.000000000 0.879376354 0.000000000 0.000000000 0.744886187
#> [13] 0.787600867 0.142672058 0.944518547 0.000000000 0.693100768 0.000000000
#> [19] 0.000000000 0.000000000 0.000000000 0.540871173 0.006912639 0.976381134
#> [25] 0.640373656 0.000000000 0.000000000 0.684419417 0.522291631 0.000000000
#> [31] 0.278243702 0.000000000 0.000000000 0.000000000 0.246976530 0.821307758
#> [37] 0.000000000 0.666890646 0.466018936 0.456394953 0.829660071 0.854634203
#> [43] 0.000000000 0.531599829 0.000000000 0.000000000 0.000000000 0.846335953
#> [49] 0.446649365 0.887603756 0.000000000 0.000000000 0.368370905 0.837991986
#> [55] 0.736284601 0.368370905 0.762052697 0.904005497 0.000000000 0.130947018
#> [61] 0.000000000 0.000000000 0.178167087 0.000000000 0.298558895 0.093531067
#> [67] 0.960518552 0.000000000 0.000000000 0.000000000 0.000000000 0.387858887
#> [73] 0.968455884 0.020860827 0.613665875 0.000000000 0.753465281 0.000000000
#> [79] 0.000000000 0.000000000 0.586773524 0.036370054 0.000000000 0.427038837
#> [85] 0.267747949 0.984266892 0.106209363 0.895813391 0.000000000 0.000000000
#> [91] 0.727657186 0.397671772 0.000000000 0.246976530 0.631469660 0.920311545
#> [97] 0.000000000 0.000000000 0.000000000 0.348502061 0.550166021 0.862915985
#> [103] 0.436874482 0.000000000 0.494318881 0.513013956 0.000000000 0.118522726
#> [109] 0.000000000 0.503694197 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.779118376 0.649247645 0.000000000 0.992139734 0.308649170
#> [121] 0.080274841 0.568542449 0.000000000 0.000000000 0.718999352 0.475516896
#> [127] 0.000000000 0.201867710 0.000000000 0.000000000 0.224987874 0.796088245
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.912176411 0.000000000
#> [139] 0.000000000 0.000000000 0.952539418 0.318644852 0.000000000 0.000000000
#> [145] 0.236117909 0.804529313 0.770582430 0.000000000 0.701722215 0.328677697
#> [151] 0.871155498 0.000000000 0.000000000 0.000000000 0.000000000 0.065734870
#> [157] 0.000000000 0.338572747 0.675684959 0.050684149 0.154512416 0.358472658
#> [163] 0.559374570 0.000000000 0.000000000 0.000000000 0.189977968 0.000000000
#> [169] 0.812910823 0.000000000 0.407438340 0.710355937 0.577676416 0.000000000
#> [175] 0.936485829 0.484909262 0.000000000 0.000000000 0.928419678 0.622583868
#> [181] 0.288505592 0.000000000 0.586773524 0.000000000 0.166456957 0.000000000
#> [187] 0.213576414 0.000000000 0.000000000
#>
#> $Time
#> 1 2 3 5 6 7 8 9 10 11 12 13 14
#> 24.00 24.00 24.00 16.43 15.64 24.00 18.43 24.00 10.53 24.00 24.00 14.34 12.89
#> 15 16 17 18 19 20 21 22 23 24 25 26 27
#> 22.68 8.71 24.00 15.21 24.00 24.00 24.00 24.00 16.92 23.89 6.32 15.77 24.00
#> 28 29 30 31 32 33 34 35 36 37 38 39 40
#> 24.00 15.45 17.43 24.00 20.90 24.00 24.00 24.00 21.19 12.52 24.00 15.59 18.00
#> 41 42 43 44 45 46 47 48 49 51 52 53 54
#> 18.02 12.43 12.10 24.00 17.42 24.00 24.00 24.00 12.19 18.23 10.42 24.00 24.00
#> 55 56 57 58 60 61 62 63 64 65 66 67 68
#> 19.34 12.21 14.46 19.34 13.15 10.12 24.00 22.77 24.00 24.00 22.13 24.00 20.62
#> 69 70 71 72 74 75 76 77 78 79 80 81 82
#> 23.23 7.38 24.00 24.00 24.00 24.00 19.22 7.27 23.88 16.23 24.00 14.06 24.00
#> 83 84 85 86 87 88 90 91 92 93 94 95 96
#> 24.00 24.00 16.44 23.81 24.00 18.37 20.94 5.33 22.92 10.33 24.00 24.00 14.54
#> 97 98 99 100 101 102 103 104 105 106 107 108 109
#> 19.14 24.00 21.19 16.07 9.97 24.00 24.00 24.00 19.75 16.67 11.18 18.29 24.00
#> 110 111 112 113 116 117 118 119 120 121 122 123 125
#> 17.56 17.45 24.00 22.86 24.00 17.46 24.00 24.00 24.00 24.00 24.00 13.00 15.65
#> 126 127 128 129 130 131 132 133 134 135 136 137 138
#> 24.00 3.53 20.35 23.41 16.47 24.00 24.00 14.65 17.81 24.00 21.83 24.00 24.00
#> 139 140 141 142 143 144 145 146 147 148 149 150 151
#> 21.49 12.68 24.00 24.00 24.00 24.00 10.07 24.00 24.00 24.00 8.37 20.33 24.00
#> 152 153 154 155 156 157 158 159 160 161 162 163 164
#> 24.00 21.33 12.63 13.08 24.00 15.10 20.14 10.55 24.00 24.00 24.00 24.00 23.60
#> 165 166 167 168 169 170 171 172 173 174 175 176 177
#> 24.00 19.98 15.55 23.72 22.41 19.54 16.57 24.00 24.00 24.00 21.91 24.00 12.53
#> 178 179 180 181 182 183 184 185 186 187 188 190 191
#> 24.00 18.63 14.82 16.46 24.00 9.24 17.77 24.00 24.00 9.92 16.16 20.81 24.00
#> 192 193 194 196 197 198 200
#> 16.44 24.00 22.40 24.00 21.60 24.00 24.00
#>
#> $bootstrap_fit
#> $bootstrap_fit[[1]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.00651030 0.02382285 -0.06241080
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.465102556 0.008159562 -0.191080503
#> grade_iii, Cure model
#> 0.942012187
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 4 17.64 1 NA 0 1
#> 36 21.19 1 48 0 1
#> 134 17.81 1 47 1 0
#> 14 12.89 1 21 0 0
#> 59 10.16 1 NA 1 0
#> 166 19.98 1 48 0 0
#> 107 11.18 1 54 1 0
#> 51 18.23 1 83 0 1
#> 197 21.60 1 69 1 0
#> 197.1 21.60 1 69 1 0
#> 69 23.23 1 25 0 1
#> 14.1 12.89 1 21 0 0
#> 50 10.02 1 NA 1 0
#> 107.1 11.18 1 54 1 0
#> 50.1 10.02 1 NA 1 0
#> 45 17.42 1 54 0 1
#> 66 22.13 1 53 0 0
#> 179 18.63 1 42 0 0
#> 100 16.07 1 60 0 0
#> 164 23.60 1 76 0 1
#> 29 15.45 1 68 1 0
#> 113 22.86 1 34 0 0
#> 52 10.42 1 52 0 1
#> 124 9.73 1 NA 1 0
#> 13 14.34 1 54 0 1
#> 88 18.37 1 47 0 0
#> 4.1 17.64 1 NA 0 1
#> 30 17.43 1 78 0 0
#> 184 17.77 1 38 0 0
#> 170 19.54 1 43 0 1
#> 52.1 10.42 1 52 0 1
#> 91 5.33 1 61 0 1
#> 188 16.16 1 46 0 1
#> 81 14.06 1 34 0 0
#> 66.1 22.13 1 53 0 0
#> 164.1 23.60 1 76 0 1
#> 153 21.33 1 55 1 0
#> 150 20.33 1 48 0 0
#> 153.1 21.33 1 55 1 0
#> 157 15.10 1 47 0 0
#> 180 14.82 1 37 0 0
#> 55 19.34 1 69 0 1
#> 50.2 10.02 1 NA 1 0
#> 187 9.92 1 39 1 0
#> 175 21.91 1 43 0 0
#> 90 20.94 1 50 0 1
#> 145 10.07 1 65 1 0
#> 58 19.34 1 39 0 0
#> 195 11.76 1 NA 1 0
#> 127 3.53 1 62 0 1
#> 81.1 14.06 1 34 0 0
#> 68 20.62 1 44 0 0
#> 190 20.81 1 42 1 0
#> 100.1 16.07 1 60 0 0
#> 179.1 18.63 1 42 0 0
#> 110 17.56 1 65 0 1
#> 41 18.02 1 40 1 0
#> 40 18.00 1 28 1 0
#> 29.1 15.45 1 68 1 0
#> 52.2 10.42 1 52 0 1
#> 189 10.51 1 NA 1 0
#> 169 22.41 1 46 0 0
#> 16 8.71 1 71 0 1
#> 10 10.53 1 34 0 0
#> 58.1 19.34 1 39 0 0
#> 133 14.65 1 57 0 0
#> 197.2 21.60 1 69 1 0
#> 189.1 10.51 1 NA 1 0
#> 114 13.68 1 NA 0 0
#> 97 19.14 1 65 0 1
#> 92 22.92 1 47 0 1
#> 134.1 17.81 1 47 1 0
#> 106 16.67 1 49 1 0
#> 16.1 8.71 1 71 0 1
#> 30.1 17.43 1 78 0 0
#> 23 16.92 1 61 0 0
#> 170.1 19.54 1 43 0 1
#> 91.1 5.33 1 61 0 1
#> 167 15.55 1 56 1 0
#> 14.2 12.89 1 21 0 0
#> 43 12.10 1 61 0 1
#> 45.1 17.42 1 54 0 1
#> 68.1 20.62 1 44 0 0
#> 93 10.33 1 52 0 1
#> 57 14.46 1 45 0 1
#> 86 23.81 1 58 0 1
#> 23.1 16.92 1 61 0 0
#> 85 16.44 1 36 0 0
#> 100.2 16.07 1 60 0 0
#> 175.1 21.91 1 43 0 0
#> 40.1 18.00 1 28 1 0
#> 79 16.23 1 54 1 0
#> 14.3 12.89 1 21 0 0
#> 170.2 19.54 1 43 0 1
#> 153.2 21.33 1 55 1 0
#> 153.3 21.33 1 55 1 0
#> 5 16.43 1 51 0 1
#> 123 13.00 1 44 1 0
#> 59.1 10.16 1 NA 1 0
#> 5.1 16.43 1 51 0 1
#> 10.1 10.53 1 34 0 0
#> 170.3 19.54 1 43 0 1
#> 139 21.49 1 63 1 0
#> 36.1 21.19 1 48 0 1
#> 125 15.65 1 67 1 0
#> 111 17.45 1 47 0 1
#> 8 18.43 1 32 0 0
#> 26 15.77 1 49 0 1
#> 32 20.90 1 37 1 0
#> 51.1 18.23 1 83 0 1
#> 199 19.81 1 NA 0 1
#> 45.2 17.42 1 54 0 1
#> 132 24.00 0 55 0 0
#> 191 24.00 0 60 0 1
#> 131 24.00 0 66 0 0
#> 148 24.00 0 61 1 0
#> 120 24.00 0 68 0 1
#> 146 24.00 0 63 1 0
#> 174 24.00 0 49 1 0
#> 20 24.00 0 46 1 0
#> 120.1 24.00 0 68 0 1
#> 82 24.00 0 34 0 0
#> 151 24.00 0 42 0 0
#> 200 24.00 0 64 0 0
#> 71 24.00 0 51 0 0
#> 35 24.00 0 51 0 0
#> 98 24.00 0 34 1 0
#> 94 24.00 0 51 0 1
#> 34 24.00 0 36 0 0
#> 33 24.00 0 53 0 0
#> 46 24.00 0 71 0 0
#> 48 24.00 0 31 1 0
#> 22 24.00 0 52 1 0
#> 178 24.00 0 52 1 0
#> 161 24.00 0 45 0 0
#> 172 24.00 0 41 0 0
#> 67 24.00 0 25 0 0
#> 31 24.00 0 36 0 1
#> 156 24.00 0 50 1 0
#> 17 24.00 0 38 0 1
#> 44 24.00 0 56 0 0
#> 1 24.00 0 23 1 0
#> 112 24.00 0 61 0 0
#> 87 24.00 0 27 0 0
#> 62 24.00 0 71 0 0
#> 174.1 24.00 0 49 1 0
#> 176 24.00 0 43 0 1
#> 71.1 24.00 0 51 0 0
#> 7 24.00 0 37 1 0
#> 147 24.00 0 76 1 0
#> 147.1 24.00 0 76 1 0
#> 67.1 24.00 0 25 0 0
#> 22.1 24.00 0 52 1 0
#> 147.2 24.00 0 76 1 0
#> 35.1 24.00 0 51 0 0
#> 122 24.00 0 66 0 0
#> 160 24.00 0 31 1 0
#> 178.1 24.00 0 52 1 0
#> 141 24.00 0 44 1 0
#> 152 24.00 0 36 0 1
#> 200.1 24.00 0 64 0 0
#> 165 24.00 0 47 0 0
#> 152.1 24.00 0 36 0 1
#> 152.2 24.00 0 36 0 1
#> 35.2 24.00 0 51 0 0
#> 71.2 24.00 0 51 0 0
#> 119 24.00 0 17 0 0
#> 152.3 24.00 0 36 0 1
#> 174.2 24.00 0 49 1 0
#> 27 24.00 0 63 1 0
#> 54 24.00 0 53 1 0
#> 109 24.00 0 48 0 0
#> 137 24.00 0 45 1 0
#> 104 24.00 0 50 1 0
#> 64 24.00 0 43 0 0
#> 165.1 24.00 0 47 0 0
#> 17.1 24.00 0 38 0 1
#> 75 24.00 0 21 1 0
#> 7.1 24.00 0 37 1 0
#> 172.1 24.00 0 41 0 0
#> 193 24.00 0 45 0 1
#> 174.3 24.00 0 49 1 0
#> 137.1 24.00 0 45 1 0
#> 132.1 24.00 0 55 0 0
#> 152.4 24.00 0 36 0 1
#> 131.1 24.00 0 66 0 0
#> 104.1 24.00 0 50 1 0
#> 44.1 24.00 0 56 0 0
#> 112.1 24.00 0 61 0 0
#> 47 24.00 0 38 0 1
#> 156.1 24.00 0 50 1 0
#> 200.2 24.00 0 64 0 0
#> 178.2 24.00 0 52 1 0
#> 172.2 24.00 0 41 0 0
#> 109.1 24.00 0 48 0 0
#> 135 24.00 0 58 1 0
#> 27.1 24.00 0 63 1 0
#> 44.2 24.00 0 56 0 0
#> 102 24.00 0 49 0 0
#> 115 24.00 0 NA 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.465 NA NA NA
#> 2 age, Cure model 0.00816 NA NA NA
#> 3 grade_ii, Cure model -0.191 NA NA NA
#> 4 grade_iii, Cure model 0.942 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00651 NA NA NA
#> 2 grade_ii, Survival model 0.0238 NA NA NA
#> 3 grade_iii, Survival model -0.0624 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.46510 0.00816 -0.19108 0.94201
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 257.1
#> Residual Deviance: 246.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.465102556 0.008159562 -0.191080503 0.942012187
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.00651030 0.02382285 -0.06241080
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.102951442 0.334613245 0.732199559 0.167099943 0.796372571 0.284386872
#> [7] 0.050769758 0.050769758 0.009070487 0.732199559 0.796372571 0.408384932
#> [13] 0.028465303 0.245966899 0.533224580 0.002966834 0.605423446 0.018107156
#> [19] 0.849222867 0.680756481 0.274592583 0.386852947 0.355115190 0.175730864
#> [25] 0.849222867 0.957967579 0.521389287 0.693593820 0.028465303 0.002966834
#> [31] 0.076131776 0.158587099 0.076131776 0.630154659 0.642709632 0.209597682
#> [37] 0.916618601 0.039222673 0.118034066 0.902920334 0.209597682 0.985872413
#> [43] 0.693593820 0.142247429 0.134070535 0.533224580 0.245966899 0.365585795
#> [49] 0.304247045 0.314415826 0.605423446 0.849222867 0.023134520 0.930359075
#> [55] 0.822713424 0.209597682 0.655317331 0.050769758 0.236494420 0.013348694
#> [61] 0.334613245 0.463592084 0.930359075 0.386852947 0.441120167 0.175730864
#> [67] 0.957967579 0.593103002 0.732199559 0.783214082 0.408384932 0.142247429
#> [73] 0.889290152 0.668000685 0.000627994 0.441120167 0.475039415 0.533224580
#> [79] 0.039222673 0.314415826 0.509635019 0.732199559 0.175730864 0.076131776
#> [85] 0.076131776 0.486544684 0.719217582 0.486544684 0.822713424 0.175730864
#> [91] 0.069146361 0.102951442 0.580856028 0.376173051 0.264889552 0.568695700
#> [97] 0.126002454 0.284386872 0.408384932 0.000000000 0.000000000 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 36 134 14 166 107 51 197 197.1 69 14.1 107.1 45 66
#> 21.19 17.81 12.89 19.98 11.18 18.23 21.60 21.60 23.23 12.89 11.18 17.42 22.13
#> 179 100 164 29 113 52 13 88 30 184 170 52.1 91
#> 18.63 16.07 23.60 15.45 22.86 10.42 14.34 18.37 17.43 17.77 19.54 10.42 5.33
#> 188 81 66.1 164.1 153 150 153.1 157 180 55 187 175 90
#> 16.16 14.06 22.13 23.60 21.33 20.33 21.33 15.10 14.82 19.34 9.92 21.91 20.94
#> 145 58 127 81.1 68 190 100.1 179.1 110 41 40 29.1 52.2
#> 10.07 19.34 3.53 14.06 20.62 20.81 16.07 18.63 17.56 18.02 18.00 15.45 10.42
#> 169 16 10 58.1 133 197.2 97 92 134.1 106 16.1 30.1 23
#> 22.41 8.71 10.53 19.34 14.65 21.60 19.14 22.92 17.81 16.67 8.71 17.43 16.92
#> 170.1 91.1 167 14.2 43 45.1 68.1 93 57 86 23.1 85 100.2
#> 19.54 5.33 15.55 12.89 12.10 17.42 20.62 10.33 14.46 23.81 16.92 16.44 16.07
#> 175.1 40.1 79 14.3 170.2 153.2 153.3 5 123 5.1 10.1 170.3 139
#> 21.91 18.00 16.23 12.89 19.54 21.33 21.33 16.43 13.00 16.43 10.53 19.54 21.49
#> 36.1 125 111 8 26 32 51.1 45.2 132 191 131 148 120
#> 21.19 15.65 17.45 18.43 15.77 20.90 18.23 17.42 24.00 24.00 24.00 24.00 24.00
#> 146 174 20 120.1 82 151 200 71 35 98 94 34 33
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 46 48 22 178 161 172 67 31 156 17 44 1 112
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87 62 174.1 176 71.1 7 147 147.1 67.1 22.1 147.2 35.1 122
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 160 178.1 141 152 200.1 165 152.1 152.2 35.2 71.2 119 152.3 174.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 27 54 109 137 104 64 165.1 17.1 75 7.1 172.1 193 174.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137.1 132.1 152.4 131.1 104.1 44.1 112.1 47 156.1 200.2 178.2 172.2 109.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135 27.1 44.2 102
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[2]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.003653336 0.149768469 0.276139515
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.235412810 0.003800764 0.330628319
#> grade_iii, Cure model
#> 0.671849623
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 6 15.64 1 39 0 0
#> 39 15.59 1 37 0 1
#> 125 15.65 1 67 1 0
#> 108 18.29 1 39 0 1
#> 40 18.00 1 28 1 0
#> 130 16.47 1 53 0 1
#> 189 10.51 1 NA 1 0
#> 45 17.42 1 54 0 1
#> 167 15.55 1 56 1 0
#> 101 9.97 1 10 0 1
#> 61 10.12 1 36 0 1
#> 192 16.44 1 31 1 0
#> 167.1 15.55 1 56 1 0
#> 85 16.44 1 36 0 0
#> 187 9.92 1 39 1 0
#> 93 10.33 1 52 0 1
#> 97 19.14 1 65 0 1
#> 159 10.55 1 50 0 1
#> 129 23.41 1 53 1 0
#> 24 23.89 1 38 0 0
#> 23 16.92 1 61 0 0
#> 42 12.43 1 49 0 1
#> 157 15.10 1 47 0 0
#> 39.1 15.59 1 37 0 1
#> 36 21.19 1 48 0 1
#> 169 22.41 1 46 0 0
#> 69 23.23 1 25 0 1
#> 30 17.43 1 78 0 0
#> 183 9.24 1 67 1 0
#> 167.2 15.55 1 56 1 0
#> 90 20.94 1 50 0 1
#> 114 13.68 1 NA 0 0
#> 100 16.07 1 60 0 0
#> 133 14.65 1 57 0 0
#> 136 21.83 1 43 0 1
#> 183.1 9.24 1 67 1 0
#> 145 10.07 1 65 1 0
#> 10 10.53 1 34 0 0
#> 150 20.33 1 48 0 0
#> 66 22.13 1 53 0 0
#> 128 20.35 1 35 0 1
#> 150.1 20.33 1 48 0 0
#> 14 12.89 1 21 0 0
#> 66.1 22.13 1 53 0 0
#> 134 17.81 1 47 1 0
#> 50 10.02 1 NA 1 0
#> 153 21.33 1 55 1 0
#> 92 22.92 1 47 0 1
#> 129.1 23.41 1 53 1 0
#> 29 15.45 1 68 1 0
#> 105 19.75 1 60 0 0
#> 183.2 9.24 1 67 1 0
#> 153.1 21.33 1 55 1 0
#> 166 19.98 1 48 0 0
#> 188 16.16 1 46 0 1
#> 183.3 9.24 1 67 1 0
#> 32 20.90 1 37 1 0
#> 192.1 16.44 1 31 1 0
#> 37 12.52 1 57 1 0
#> 130.1 16.47 1 53 0 1
#> 150.2 20.33 1 48 0 0
#> 10.1 10.53 1 34 0 0
#> 167.3 15.55 1 56 1 0
#> 6.1 15.64 1 39 0 0
#> 6.2 15.64 1 39 0 0
#> 61.1 10.12 1 36 0 1
#> 78 23.88 1 43 0 0
#> 155 13.08 1 26 0 0
#> 101.1 9.97 1 10 0 1
#> 114.1 13.68 1 NA 0 0
#> 192.2 16.44 1 31 1 0
#> 63 22.77 1 31 1 0
#> 127 3.53 1 62 0 1
#> 8 18.43 1 32 0 0
#> 43 12.10 1 61 0 1
#> 139 21.49 1 63 1 0
#> 51 18.23 1 83 0 1
#> 167.4 15.55 1 56 1 0
#> 32.1 20.90 1 37 1 0
#> 61.2 10.12 1 36 0 1
#> 123 13.00 1 44 1 0
#> 56 12.21 1 60 0 0
#> 40.1 18.00 1 28 1 0
#> 199 19.81 1 NA 0 1
#> 29.1 15.45 1 68 1 0
#> 90.1 20.94 1 50 0 1
#> 25 6.32 1 34 1 0
#> 88 18.37 1 47 0 0
#> 89 11.44 1 NA 0 0
#> 180 14.82 1 37 0 0
#> 175 21.91 1 43 0 0
#> 40.2 18.00 1 28 1 0
#> 52 10.42 1 52 0 1
#> 195 11.76 1 NA 1 0
#> 16 8.71 1 71 0 1
#> 63.1 22.77 1 31 1 0
#> 96 14.54 1 33 0 1
#> 5 16.43 1 51 0 1
#> 187.1 9.92 1 39 1 0
#> 155.1 13.08 1 26 0 0
#> 197 21.60 1 69 1 0
#> 127.1 3.53 1 62 0 1
#> 86 23.81 1 58 0 1
#> 66.2 22.13 1 53 0 0
#> 128.1 20.35 1 35 0 1
#> 107 11.18 1 54 1 0
#> 159.1 10.55 1 50 0 1
#> 100.1 16.07 1 60 0 0
#> 10.2 10.53 1 34 0 0
#> 99 21.19 1 38 0 1
#> 133.1 14.65 1 57 0 0
#> 129.2 23.41 1 53 1 0
#> 182 24.00 0 35 0 0
#> 160 24.00 0 31 1 0
#> 72 24.00 0 40 0 1
#> 94 24.00 0 51 0 1
#> 172 24.00 0 41 0 0
#> 19 24.00 0 57 0 1
#> 11 24.00 0 42 0 1
#> 131 24.00 0 66 0 0
#> 95 24.00 0 68 0 1
#> 176 24.00 0 43 0 1
#> 162 24.00 0 51 0 0
#> 73 24.00 0 NA 0 1
#> 28 24.00 0 67 1 0
#> 73.1 24.00 0 NA 0 1
#> 115 24.00 0 NA 1 0
#> 151 24.00 0 42 0 0
#> 22 24.00 0 52 1 0
#> 200 24.00 0 64 0 0
#> 161 24.00 0 45 0 0
#> 185 24.00 0 44 1 0
#> 80 24.00 0 41 0 0
#> 115.1 24.00 0 NA 1 0
#> 165 24.00 0 47 0 0
#> 46 24.00 0 71 0 0
#> 118 24.00 0 44 1 0
#> 137 24.00 0 45 1 0
#> 98 24.00 0 34 1 0
#> 102 24.00 0 49 0 0
#> 22.1 24.00 0 52 1 0
#> 109 24.00 0 48 0 0
#> 87 24.00 0 27 0 0
#> 38 24.00 0 31 1 0
#> 95.1 24.00 0 68 0 1
#> 47 24.00 0 38 0 1
#> 75 24.00 0 21 1 0
#> 38.1 24.00 0 31 1 0
#> 165.1 24.00 0 47 0 0
#> 2 24.00 0 9 0 0
#> 151.1 24.00 0 42 0 0
#> 109.1 24.00 0 48 0 0
#> 12 24.00 0 63 0 0
#> 126 24.00 0 48 0 0
#> 47.1 24.00 0 38 0 1
#> 146 24.00 0 63 1 0
#> 31 24.00 0 36 0 1
#> 161.1 24.00 0 45 0 0
#> 178 24.00 0 52 1 0
#> 121 24.00 0 57 1 0
#> 122 24.00 0 66 0 0
#> 131.1 24.00 0 66 0 0
#> 33 24.00 0 53 0 0
#> 178.1 24.00 0 52 1 0
#> 83 24.00 0 6 0 0
#> 27 24.00 0 63 1 0
#> 174 24.00 0 49 1 0
#> 33.1 24.00 0 53 0 0
#> 35 24.00 0 51 0 0
#> 31.1 24.00 0 36 0 1
#> 19.1 24.00 0 57 0 1
#> 19.2 24.00 0 57 0 1
#> 112 24.00 0 61 0 0
#> 185.1 24.00 0 44 1 0
#> 65 24.00 0 57 1 0
#> 103 24.00 0 56 1 0
#> 156 24.00 0 50 1 0
#> 46.1 24.00 0 71 0 0
#> 138 24.00 0 44 1 0
#> 7 24.00 0 37 1 0
#> 162.1 24.00 0 51 0 0
#> 95.2 24.00 0 68 0 1
#> 115.2 24.00 0 NA 1 0
#> 83.1 24.00 0 6 0 0
#> 9 24.00 0 31 1 0
#> 53 24.00 0 32 0 1
#> 163 24.00 0 66 0 0
#> 118.1 24.00 0 44 1 0
#> 115.3 24.00 0 NA 1 0
#> 80.1 24.00 0 41 0 0
#> 173 24.00 0 19 0 1
#> 121.1 24.00 0 57 1 0
#> 141 24.00 0 44 1 0
#> 53.1 24.00 0 32 0 1
#> 33.2 24.00 0 53 0 0
#> 46.2 24.00 0 71 0 0
#> 2.1 24.00 0 9 0 0
#> 176.1 24.00 0 43 0 1
#> 137.1 24.00 0 45 1 0
#> 74 24.00 0 43 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.235 NA NA NA
#> 2 age, Cure model 0.00380 NA NA NA
#> 3 grade_ii, Cure model 0.331 NA NA NA
#> 4 grade_iii, Cure model 0.672 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00365 NA NA NA
#> 2 grade_ii, Survival model 0.150 NA NA NA
#> 3 grade_iii, Survival model 0.276 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.235413 0.003801 0.330628 0.671850
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 256.4
#> Residual Deviance: 253 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.235412810 0.003800764 0.330628319 0.671849623
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.003653336 0.149768469 0.276139515
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.63669752 0.66085117 0.62849406 0.46494807 0.48338987 0.54527720
#> [7] 0.52772245 0.67685373 0.91663279 0.88811435 0.56232960 0.67685373
#> [13] 0.56232960 0.93080011 0.88084558 0.43668424 0.83703069 0.09382369
#> [19] 0.01981700 0.53651775 0.80706310 0.73063842 0.66085117 0.30823035
#> [25] 0.18993254 0.13540712 0.51883750 0.94489461 0.67685373 0.32932957
#> [31] 0.61209134 0.74610927 0.25093700 0.94489461 0.90948082 0.85170255
#> [37] 0.38906636 0.20305250 0.36962961 0.38906636 0.79188311 0.20305250
#> [43] 0.50990210 0.28631837 0.15023804 0.09382369 0.71520739 0.42709504
#> [49] 0.94489461 0.28631837 0.41745280 0.60377934 0.94489461 0.34967077
#> [55] 0.56232960 0.79948861 0.54527720 0.38906636 0.85170255 0.67685373
#> [61] 0.63669752 0.63669752 0.88811435 0.04731932 0.76906951 0.91663279
#> [67] 0.56232960 0.16428714 0.98633359 0.44613414 0.82211353 0.27476606
#> [73] 0.47423932 0.67685373 0.34967077 0.88811435 0.78427177 0.81459683
#> [79] 0.48338987 0.71520739 0.32932957 0.97941371 0.45555930 0.73837971
#> [85] 0.23856722 0.48338987 0.87354102 0.97247839 0.16428714 0.76141530
#> [91] 0.59540286 0.93080011 0.76906951 0.26298493 0.98633359 0.07283040
#> [97] 0.20305250 0.36962961 0.82958602 0.83703069 0.61209134 0.85170255
#> [103] 0.30823035 0.74610927 0.09382369 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000
#>
#> $Time
#> 6 39 125 108 40 130 45 167 101 61 192 167.1 85
#> 15.64 15.59 15.65 18.29 18.00 16.47 17.42 15.55 9.97 10.12 16.44 15.55 16.44
#> 187 93 97 159 129 24 23 42 157 39.1 36 169 69
#> 9.92 10.33 19.14 10.55 23.41 23.89 16.92 12.43 15.10 15.59 21.19 22.41 23.23
#> 30 183 167.2 90 100 133 136 183.1 145 10 150 66 128
#> 17.43 9.24 15.55 20.94 16.07 14.65 21.83 9.24 10.07 10.53 20.33 22.13 20.35
#> 150.1 14 66.1 134 153 92 129.1 29 105 183.2 153.1 166 188
#> 20.33 12.89 22.13 17.81 21.33 22.92 23.41 15.45 19.75 9.24 21.33 19.98 16.16
#> 183.3 32 192.1 37 130.1 150.2 10.1 167.3 6.1 6.2 61.1 78 155
#> 9.24 20.90 16.44 12.52 16.47 20.33 10.53 15.55 15.64 15.64 10.12 23.88 13.08
#> 101.1 192.2 63 127 8 43 139 51 167.4 32.1 61.2 123 56
#> 9.97 16.44 22.77 3.53 18.43 12.10 21.49 18.23 15.55 20.90 10.12 13.00 12.21
#> 40.1 29.1 90.1 25 88 180 175 40.2 52 16 63.1 96 5
#> 18.00 15.45 20.94 6.32 18.37 14.82 21.91 18.00 10.42 8.71 22.77 14.54 16.43
#> 187.1 155.1 197 127.1 86 66.2 128.1 107 159.1 100.1 10.2 99 133.1
#> 9.92 13.08 21.60 3.53 23.81 22.13 20.35 11.18 10.55 16.07 10.53 21.19 14.65
#> 129.2 182 160 72 94 172 19 11 131 95 176 162 28
#> 23.41 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 151 22 200 161 185 80 165 46 118 137 98 102 22.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 109 87 38 95.1 47 75 38.1 165.1 2 151.1 109.1 12 126
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 47.1 146 31 161.1 178 121 122 131.1 33 178.1 83 27 174
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33.1 35 31.1 19.1 19.2 112 185.1 65 103 156 46.1 138 7
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 162.1 95.2 83.1 9 53 163 118.1 80.1 173 121.1 141 53.1 33.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 46.2 2.1 176.1 137.1 74
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[3]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01126472 0.56929253 0.23493698
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.53681406 0.00734337 0.42279228
#> grade_iii, Cure model
#> 0.82124922
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 153 21.33 1 55 1 0
#> 140 12.68 1 59 1 0
#> 167 15.55 1 56 1 0
#> 136 21.83 1 43 0 1
#> 49 12.19 1 48 1 0
#> 57 14.46 1 45 0 1
#> 10 10.53 1 34 0 0
#> 169 22.41 1 46 0 0
#> 166 19.98 1 48 0 0
#> 81 14.06 1 34 0 0
#> 70 7.38 1 30 1 0
#> 166.1 19.98 1 48 0 0
#> 23 16.92 1 61 0 0
#> 88 18.37 1 47 0 0
#> 8 18.43 1 32 0 0
#> 69 23.23 1 25 0 1
#> 167.1 15.55 1 56 1 0
#> 37 12.52 1 57 1 0
#> 32 20.90 1 37 1 0
#> 92 22.92 1 47 0 1
#> 140.1 12.68 1 59 1 0
#> 70.1 7.38 1 30 1 0
#> 55 19.34 1 69 0 1
#> 36 21.19 1 48 0 1
#> 77 7.27 1 67 0 1
#> 114 13.68 1 NA 0 0
#> 88.1 18.37 1 47 0 0
#> 128 20.35 1 35 0 1
#> 45 17.42 1 54 0 1
#> 89 11.44 1 NA 0 0
#> 32.1 20.90 1 37 1 0
#> 105 19.75 1 60 0 0
#> 171 16.57 1 41 0 1
#> 88.2 18.37 1 47 0 0
#> 50 10.02 1 NA 1 0
#> 49.1 12.19 1 48 1 0
#> 45.1 17.42 1 54 0 1
#> 150 20.33 1 48 0 0
#> 50.1 10.02 1 NA 1 0
#> 181 16.46 1 45 0 1
#> 37.1 12.52 1 57 1 0
#> 26 15.77 1 49 0 1
#> 153.1 21.33 1 55 1 0
#> 96 14.54 1 33 0 1
#> 100 16.07 1 60 0 0
#> 150.1 20.33 1 48 0 0
#> 32.2 20.90 1 37 1 0
#> 139 21.49 1 63 1 0
#> 123 13.00 1 44 1 0
#> 23.1 16.92 1 61 0 0
#> 154 12.63 1 20 1 0
#> 58 19.34 1 39 0 0
#> 66 22.13 1 53 0 0
#> 117 17.46 1 26 0 1
#> 24 23.89 1 38 0 0
#> 60 13.15 1 38 1 0
#> 91 5.33 1 61 0 1
#> 188 16.16 1 46 0 1
#> 32.3 20.90 1 37 1 0
#> 171.1 16.57 1 41 0 1
#> 189 10.51 1 NA 1 0
#> 199 19.81 1 NA 0 1
#> 155 13.08 1 26 0 0
#> 139.1 21.49 1 63 1 0
#> 45.2 17.42 1 54 0 1
#> 79 16.23 1 54 1 0
#> 70.2 7.38 1 30 1 0
#> 187 9.92 1 39 1 0
#> 195 11.76 1 NA 1 0
#> 96.1 14.54 1 33 0 1
#> 43 12.10 1 61 0 1
#> 52 10.42 1 52 0 1
#> 177 12.53 1 75 0 0
#> 189.1 10.51 1 NA 1 0
#> 52.1 10.42 1 52 0 1
#> 85 16.44 1 36 0 0
#> 171.2 16.57 1 41 0 1
#> 14 12.89 1 21 0 0
#> 78 23.88 1 43 0 0
#> 92.1 22.92 1 47 0 1
#> 167.2 15.55 1 56 1 0
#> 78.1 23.88 1 43 0 0
#> 150.2 20.33 1 48 0 0
#> 29 15.45 1 68 1 0
#> 157 15.10 1 47 0 0
#> 58.1 19.34 1 39 0 0
#> 106 16.67 1 49 1 0
#> 23.2 16.92 1 61 0 0
#> 192 16.44 1 31 1 0
#> 183 9.24 1 67 1 0
#> 197 21.60 1 69 1 0
#> 57.1 14.46 1 45 0 1
#> 105.1 19.75 1 60 0 0
#> 167.3 15.55 1 56 1 0
#> 108 18.29 1 39 0 1
#> 159 10.55 1 50 0 1
#> 89.1 11.44 1 NA 0 0
#> 167.4 15.55 1 56 1 0
#> 153.2 21.33 1 55 1 0
#> 139.2 21.49 1 63 1 0
#> 183.1 9.24 1 67 1 0
#> 10.1 10.53 1 34 0 0
#> 4 17.64 1 NA 0 1
#> 197.1 21.60 1 69 1 0
#> 8.1 18.43 1 32 0 0
#> 14.1 12.89 1 21 0 0
#> 29.1 15.45 1 68 1 0
#> 164 23.60 1 76 0 1
#> 149 8.37 1 33 1 0
#> 149.1 8.37 1 33 1 0
#> 10.2 10.53 1 34 0 0
#> 111 17.45 1 47 0 1
#> 19 24.00 0 57 0 1
#> 132 24.00 0 55 0 0
#> 44 24.00 0 56 0 0
#> 9 24.00 0 31 1 0
#> 44.1 24.00 0 56 0 0
#> 173 24.00 0 19 0 1
#> 182 24.00 0 35 0 0
#> 84 24.00 0 39 0 1
#> 35 24.00 0 51 0 0
#> 121 24.00 0 57 1 0
#> 44.2 24.00 0 56 0 0
#> 132.1 24.00 0 55 0 0
#> 47 24.00 0 38 0 1
#> 147 24.00 0 76 1 0
#> 46 24.00 0 71 0 0
#> 141 24.00 0 44 1 0
#> 147.1 24.00 0 76 1 0
#> 132.2 24.00 0 55 0 0
#> 174 24.00 0 49 1 0
#> 98 24.00 0 34 1 0
#> 142 24.00 0 53 0 0
#> 75 24.00 0 21 1 0
#> 137 24.00 0 45 1 0
#> 38 24.00 0 31 1 0
#> 161 24.00 0 45 0 0
#> 102 24.00 0 49 0 0
#> 141.1 24.00 0 44 1 0
#> 143 24.00 0 51 0 0
#> 44.3 24.00 0 56 0 0
#> 146 24.00 0 63 1 0
#> 143.1 24.00 0 51 0 0
#> 191 24.00 0 60 0 1
#> 186 24.00 0 45 1 0
#> 82 24.00 0 34 0 0
#> 137.1 24.00 0 45 1 0
#> 112 24.00 0 61 0 0
#> 120 24.00 0 68 0 1
#> 193 24.00 0 45 0 1
#> 118 24.00 0 44 1 0
#> 74 24.00 0 43 0 1
#> 87 24.00 0 27 0 0
#> 152 24.00 0 36 0 1
#> 46.1 24.00 0 71 0 0
#> 53 24.00 0 32 0 1
#> 2 24.00 0 9 0 0
#> 102.1 24.00 0 49 0 0
#> 33 24.00 0 53 0 0
#> 126 24.00 0 48 0 0
#> 131 24.00 0 66 0 0
#> 156 24.00 0 50 1 0
#> 104 24.00 0 50 1 0
#> 122 24.00 0 66 0 0
#> 176 24.00 0 43 0 1
#> 46.2 24.00 0 71 0 0
#> 67 24.00 0 25 0 0
#> 98.1 24.00 0 34 1 0
#> 119 24.00 0 17 0 0
#> 137.2 24.00 0 45 1 0
#> 144 24.00 0 28 0 1
#> 7 24.00 0 37 1 0
#> 103 24.00 0 56 1 0
#> 98.2 24.00 0 34 1 0
#> 163 24.00 0 66 0 0
#> 142.1 24.00 0 53 0 0
#> 120.1 24.00 0 68 0 1
#> 191.1 24.00 0 60 0 1
#> 11 24.00 0 42 0 1
#> 137.3 24.00 0 45 1 0
#> 73 24.00 0 NA 0 1
#> 64 24.00 0 43 0 0
#> 137.4 24.00 0 45 1 0
#> 102.2 24.00 0 49 0 0
#> 75.1 24.00 0 21 1 0
#> 191.2 24.00 0 60 0 1
#> 44.4 24.00 0 56 0 0
#> 75.2 24.00 0 21 1 0
#> 7.1 24.00 0 37 1 0
#> 35.1 24.00 0 51 0 0
#> 82.1 24.00 0 34 0 0
#> 33.1 24.00 0 53 0 0
#> 34 24.00 0 36 0 0
#> 67.1 24.00 0 25 0 0
#> 104.1 24.00 0 50 1 0
#> 44.5 24.00 0 56 0 0
#> 75.3 24.00 0 21 1 0
#> 118.1 24.00 0 44 1 0
#> 82.2 24.00 0 34 0 0
#> 7.2 24.00 0 37 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.537 NA NA NA
#> 2 age, Cure model 0.00734 NA NA NA
#> 3 grade_ii, Cure model 0.423 NA NA NA
#> 4 grade_iii, Cure model 0.821 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0113 NA NA NA
#> 2 grade_ii, Survival model 0.569 NA NA NA
#> 3 grade_iii, Survival model 0.235 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.536814 0.007343 0.422792 0.821249
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.8
#> Residual Deviance: 255.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.53681406 0.00734337 0.42279228 0.82124922
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01126472 0.56929253 0.23493698
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.0928012743 0.7032793538 0.5004622853 0.0481036191 0.7733293797
#> [6] 0.6107800304 0.8203954227 0.0339162254 0.1830110128 0.6336534779
#> [11] 0.9404233229 0.1830110128 0.3501215829 0.2620310413 0.2435323822
#> [16] 0.0167197224 0.5004622853 0.7499506965 0.1233606472 0.0224845887
#> [21] 0.7032793538 0.9404233229 0.2169185299 0.1152004858 0.9758900455
#> [26] 0.2620310413 0.1518178303 0.3202609952 0.1233606472 0.1996109865
#> [31] 0.3919909177 0.2620310413 0.7733293797 0.3202609952 0.1595527685
#> [36] 0.4236966351 0.7499506965 0.4892661275 0.0928012743 0.5881088339
#> [41] 0.4781391578 0.1595527685 0.1233606472 0.0706885372 0.6684697243
#> [46] 0.3501215829 0.7265446682 0.2169185299 0.0407317953 0.3003825075
#> [51] 0.0008250494 0.6452626045 0.9879182664 0.4671379713 0.1233606472
#> [56] 0.3919909177 0.6568401407 0.0706885372 0.3202609952 0.4562003296
#> [61] 0.9404233229 0.8801062490 0.5881088339 0.7966876409 0.8560017794
#> [66] 0.7381947701 0.8560017794 0.4346068683 0.3919909177 0.6800838714
#> [71] 0.0038265551 0.0224845887 0.5004622853 0.0038265551 0.1595527685
#> [76] 0.5543428778 0.5767185769 0.2169185299 0.3813047661 0.3501215829
#> [81] 0.4346068683 0.8922189769 0.0557355058 0.6107800304 0.1996109865
#> [86] 0.5004622853 0.2905022409 0.8085172126 0.5004622853 0.0928012743
#> [91] 0.0706885372 0.8922189769 0.8203954227 0.0557355058 0.2435323822
#> [96] 0.6800838714 0.5543428778 0.0110626761 0.9163903578 0.9163903578
#> [101] 0.8203954227 0.3102811320 0.0000000000 0.0000000000 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#>
#> $Time
#> 153 140 167 136 49 57 10 169 166 81 70 166.1 23
#> 21.33 12.68 15.55 21.83 12.19 14.46 10.53 22.41 19.98 14.06 7.38 19.98 16.92
#> 88 8 69 167.1 37 32 92 140.1 70.1 55 36 77 88.1
#> 18.37 18.43 23.23 15.55 12.52 20.90 22.92 12.68 7.38 19.34 21.19 7.27 18.37
#> 128 45 32.1 105 171 88.2 49.1 45.1 150 181 37.1 26 153.1
#> 20.35 17.42 20.90 19.75 16.57 18.37 12.19 17.42 20.33 16.46 12.52 15.77 21.33
#> 96 100 150.1 32.2 139 123 23.1 154 58 66 117 24 60
#> 14.54 16.07 20.33 20.90 21.49 13.00 16.92 12.63 19.34 22.13 17.46 23.89 13.15
#> 91 188 32.3 171.1 155 139.1 45.2 79 70.2 187 96.1 43 52
#> 5.33 16.16 20.90 16.57 13.08 21.49 17.42 16.23 7.38 9.92 14.54 12.10 10.42
#> 177 52.1 85 171.2 14 78 92.1 167.2 78.1 150.2 29 157 58.1
#> 12.53 10.42 16.44 16.57 12.89 23.88 22.92 15.55 23.88 20.33 15.45 15.10 19.34
#> 106 23.2 192 183 197 57.1 105.1 167.3 108 159 167.4 153.2 139.2
#> 16.67 16.92 16.44 9.24 21.60 14.46 19.75 15.55 18.29 10.55 15.55 21.33 21.49
#> 183.1 10.1 197.1 8.1 14.1 29.1 164 149 149.1 10.2 111 19 132
#> 9.24 10.53 21.60 18.43 12.89 15.45 23.60 8.37 8.37 10.53 17.45 24.00 24.00
#> 44 9 44.1 173 182 84 35 121 44.2 132.1 47 147 46
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 141 147.1 132.2 174 98 142 75 137 38 161 102 141.1 143
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44.3 146 143.1 191 186 82 137.1 112 120 193 118 74 87
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152 46.1 53 2 102.1 33 126 131 156 104 122 176 46.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67 98.1 119 137.2 144 7 103 98.2 163 142.1 120.1 191.1 11
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137.3 64 137.4 102.2 75.1 191.2 44.4 75.2 7.1 35.1 82.1 33.1 34
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67.1 104.1 44.5 75.3 118.1 82.2 7.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[4]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.005153665 0.882714045 0.497877358
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.21522101 0.02298384 0.38332376
#> grade_iii, Cure model
#> 0.65868891
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 88 18.37 1 47 0 0
#> 168 23.72 1 70 0 0
#> 61 10.12 1 36 0 1
#> 50 10.02 1 NA 1 0
#> 99 21.19 1 38 0 1
#> 14 12.89 1 21 0 0
#> 78 23.88 1 43 0 0
#> 60 13.15 1 38 1 0
#> 5 16.43 1 51 0 1
#> 61.1 10.12 1 36 0 1
#> 139 21.49 1 63 1 0
#> 36 21.19 1 48 0 1
#> 4 17.64 1 NA 0 1
#> 85 16.44 1 36 0 0
#> 177 12.53 1 75 0 0
#> 166 19.98 1 48 0 0
#> 55 19.34 1 69 0 1
#> 49 12.19 1 48 1 0
#> 16 8.71 1 71 0 1
#> 60.1 13.15 1 38 1 0
#> 183 9.24 1 67 1 0
#> 139.1 21.49 1 63 1 0
#> 183.1 9.24 1 67 1 0
#> 41 18.02 1 40 1 0
#> 43 12.10 1 61 0 1
#> 164 23.60 1 76 0 1
#> 195 11.76 1 NA 1 0
#> 49.1 12.19 1 48 1 0
#> 90 20.94 1 50 0 1
#> 89 11.44 1 NA 0 0
#> 154 12.63 1 20 1 0
#> 86 23.81 1 58 0 1
#> 60.2 13.15 1 38 1 0
#> 56 12.21 1 60 0 0
#> 58 19.34 1 39 0 0
#> 13 14.34 1 54 0 1
#> 43.1 12.10 1 61 0 1
#> 167 15.55 1 56 1 0
#> 155 13.08 1 26 0 0
#> 123 13.00 1 44 1 0
#> 99.1 21.19 1 38 0 1
#> 56.1 12.21 1 60 0 0
#> 100 16.07 1 60 0 0
#> 63 22.77 1 31 1 0
#> 199 19.81 1 NA 0 1
#> 183.2 9.24 1 67 1 0
#> 24 23.89 1 38 0 0
#> 181 16.46 1 45 0 1
#> 194 22.40 1 38 0 1
#> 41.1 18.02 1 40 1 0
#> 197 21.60 1 69 1 0
#> 63.1 22.77 1 31 1 0
#> 78.1 23.88 1 43 0 0
#> 26 15.77 1 49 0 1
#> 96 14.54 1 33 0 1
#> 58.1 19.34 1 39 0 0
#> 183.3 9.24 1 67 1 0
#> 125 15.65 1 67 1 0
#> 129 23.41 1 53 1 0
#> 90.1 20.94 1 50 0 1
#> 40 18.00 1 28 1 0
#> 24.1 23.89 1 38 0 0
#> 43.2 12.10 1 61 0 1
#> 55.1 19.34 1 69 0 1
#> 76 19.22 1 54 0 1
#> 101 9.97 1 10 0 1
#> 145 10.07 1 65 1 0
#> 85.1 16.44 1 36 0 0
#> 42 12.43 1 49 0 1
#> 99.2 21.19 1 38 0 1
#> 192 16.44 1 31 1 0
#> 24.2 23.89 1 38 0 0
#> 89.1 11.44 1 NA 0 0
#> 63.2 22.77 1 31 1 0
#> 49.2 12.19 1 48 1 0
#> 58.2 19.34 1 39 0 0
#> 188 16.16 1 46 0 1
#> 56.2 12.21 1 60 0 0
#> 113 22.86 1 34 0 0
#> 124 9.73 1 NA 1 0
#> 52 10.42 1 52 0 1
#> 106 16.67 1 49 1 0
#> 40.1 18.00 1 28 1 0
#> 195.1 11.76 1 NA 1 0
#> 183.4 9.24 1 67 1 0
#> 14.1 12.89 1 21 0 0
#> 50.1 10.02 1 NA 1 0
#> 145.1 10.07 1 65 1 0
#> 106.1 16.67 1 49 1 0
#> 117 17.46 1 26 0 1
#> 78.2 23.88 1 43 0 0
#> 86.1 23.81 1 58 0 1
#> 41.2 18.02 1 40 1 0
#> 134 17.81 1 47 1 0
#> 29 15.45 1 68 1 0
#> 51 18.23 1 83 0 1
#> 180 14.82 1 37 0 0
#> 57 14.46 1 45 0 1
#> 195.2 11.76 1 NA 1 0
#> 189 10.51 1 NA 1 0
#> 25 6.32 1 34 1 0
#> 40.2 18.00 1 28 1 0
#> 170 19.54 1 43 0 1
#> 177.1 12.53 1 75 0 0
#> 51.1 18.23 1 83 0 1
#> 164.1 23.60 1 76 0 1
#> 49.3 12.19 1 48 1 0
#> 113.1 22.86 1 34 0 0
#> 30 17.43 1 78 0 0
#> 32 20.90 1 37 1 0
#> 15 22.68 1 48 0 0
#> 128 20.35 1 35 0 1
#> 143 24.00 0 51 0 0
#> 53 24.00 0 32 0 1
#> 104 24.00 0 50 1 0
#> 118 24.00 0 44 1 0
#> 191 24.00 0 60 0 1
#> 176 24.00 0 43 0 1
#> 102 24.00 0 49 0 0
#> 9 24.00 0 31 1 0
#> 1 24.00 0 23 1 0
#> 126 24.00 0 48 0 0
#> 173 24.00 0 19 0 1
#> 163 24.00 0 66 0 0
#> 165 24.00 0 47 0 0
#> 112 24.00 0 61 0 0
#> 196 24.00 0 19 0 0
#> 165.1 24.00 0 47 0 0
#> 54 24.00 0 53 1 0
#> 119 24.00 0 17 0 0
#> 116 24.00 0 58 0 1
#> 112.1 24.00 0 61 0 0
#> 144 24.00 0 28 0 1
#> 73 24.00 0 NA 0 1
#> 126.1 24.00 0 48 0 0
#> 144.1 24.00 0 28 0 1
#> 152 24.00 0 36 0 1
#> 152.1 24.00 0 36 0 1
#> 132 24.00 0 55 0 0
#> 148 24.00 0 61 1 0
#> 176.1 24.00 0 43 0 1
#> 120 24.00 0 68 0 1
#> 83 24.00 0 6 0 0
#> 131 24.00 0 66 0 0
#> 119.1 24.00 0 17 0 0
#> 193 24.00 0 45 0 1
#> 3 24.00 0 31 1 0
#> 46 24.00 0 71 0 0
#> 19 24.00 0 57 0 1
#> 7 24.00 0 37 1 0
#> 178 24.00 0 52 1 0
#> 112.2 24.00 0 61 0 0
#> 173.1 24.00 0 19 0 1
#> 119.2 24.00 0 17 0 0
#> 72 24.00 0 40 0 1
#> 20 24.00 0 46 1 0
#> 21 24.00 0 47 0 0
#> 196.1 24.00 0 19 0 0
#> 1.1 24.00 0 23 1 0
#> 162 24.00 0 51 0 0
#> 148.1 24.00 0 61 1 0
#> 98 24.00 0 34 1 0
#> 165.2 24.00 0 47 0 0
#> 152.2 24.00 0 36 0 1
#> 147 24.00 0 76 1 0
#> 46.1 24.00 0 71 0 0
#> 47 24.00 0 38 0 1
#> 160 24.00 0 31 1 0
#> 67 24.00 0 25 0 0
#> 27 24.00 0 63 1 0
#> 21.1 24.00 0 47 0 0
#> 84 24.00 0 39 0 1
#> 186 24.00 0 45 1 0
#> 162.1 24.00 0 51 0 0
#> 94 24.00 0 51 0 1
#> 147.1 24.00 0 76 1 0
#> 22 24.00 0 52 1 0
#> 148.2 24.00 0 61 1 0
#> 119.3 24.00 0 17 0 0
#> 48 24.00 0 31 1 0
#> 20.1 24.00 0 46 1 0
#> 20.2 24.00 0 46 1 0
#> 182 24.00 0 35 0 0
#> 138 24.00 0 44 1 0
#> 73.1 24.00 0 NA 0 1
#> 2 24.00 0 9 0 0
#> 67.1 24.00 0 25 0 0
#> 161 24.00 0 45 0 0
#> 75 24.00 0 21 1 0
#> 83.1 24.00 0 6 0 0
#> 53.1 24.00 0 32 0 1
#> 138.1 24.00 0 44 1 0
#> 74 24.00 0 43 0 1
#> 186.1 24.00 0 45 1 0
#> 162.2 24.00 0 51 0 0
#> 64 24.00 0 43 0 0
#> 38 24.00 0 31 1 0
#> 9.1 24.00 0 31 1 0
#> 2.1 24.00 0 9 0 0
#> 147.2 24.00 0 76 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.22 NA NA NA
#> 2 age, Cure model 0.0230 NA NA NA
#> 3 grade_ii, Cure model 0.383 NA NA NA
#> 4 grade_iii, Cure model 0.659 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00515 NA NA NA
#> 2 grade_ii, Survival model 0.883 NA NA NA
#> 3 grade_iii, Survival model 0.498 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.21522 0.02298 0.38332 0.65869
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 258
#> Residual Deviance: 247.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.21522101 0.02298384 0.38332376 0.65868891
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.005153665 0.882714045 0.497877358
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.64024030 0.29063606 0.94562541 0.49762230 0.85879531 0.16356897
#> [7] 0.83160706 0.76590535 0.94562541 0.47627862 0.49762230 0.74705199
#> [13] 0.87488092 0.57311747 0.59097655 0.90634613 0.99123692 0.83160706
#> [19] 0.96930058 0.47627862 0.96930058 0.66429940 0.92615713 0.31339401
#> [25] 0.90634613 0.53608038 0.86954496 0.24542979 0.83160706 0.89072952
#> [31] 0.59097655 0.82591321 0.92615713 0.79679740 0.84792597 0.85339581
#> [37] 0.49762230 0.89072952 0.77840552 0.39905661 0.96930058 0.07188664
#> [43] 0.74059092 0.45130122 0.66429940 0.46420099 0.39905661 0.16356897
#> [49] 0.78461018 0.81438916 0.59097655 0.96930058 0.79076048 0.34993940
#> [55] 0.53608038 0.68632077 0.07188664 0.92615713 0.59097655 0.63195322
#> [61] 0.96461466 0.95523229 0.74705199 0.88545959 0.49762230 0.74705199
#> [67] 0.07188664 0.39905661 0.90634613 0.59097655 0.77218289 0.89072952
#> [73] 0.36675272 0.94076112 0.72760392 0.68632077 0.96930058 0.85879531
#> [79] 0.95523229 0.72760392 0.71401335 0.16356897 0.24542979 0.66429940
#> [85] 0.70714448 0.80273420 0.64849809 0.80856609 0.82017294 0.99563659
#> [91] 0.68632077 0.58211915 0.87488092 0.64849809 0.31339401 0.90634613
#> [97] 0.36675272 0.72082448 0.55489156 0.43802148 0.56407595 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000
#>
#> $Time
#> 88 168 61 99 14 78 60 5 61.1 139 36 85 177
#> 18.37 23.72 10.12 21.19 12.89 23.88 13.15 16.43 10.12 21.49 21.19 16.44 12.53
#> 166 55 49 16 60.1 183 139.1 183.1 41 43 164 49.1 90
#> 19.98 19.34 12.19 8.71 13.15 9.24 21.49 9.24 18.02 12.10 23.60 12.19 20.94
#> 154 86 60.2 56 58 13 43.1 167 155 123 99.1 56.1 100
#> 12.63 23.81 13.15 12.21 19.34 14.34 12.10 15.55 13.08 13.00 21.19 12.21 16.07
#> 63 183.2 24 181 194 41.1 197 63.1 78.1 26 96 58.1 183.3
#> 22.77 9.24 23.89 16.46 22.40 18.02 21.60 22.77 23.88 15.77 14.54 19.34 9.24
#> 125 129 90.1 40 24.1 43.2 55.1 76 101 145 85.1 42 99.2
#> 15.65 23.41 20.94 18.00 23.89 12.10 19.34 19.22 9.97 10.07 16.44 12.43 21.19
#> 192 24.2 63.2 49.2 58.2 188 56.2 113 52 106 40.1 183.4 14.1
#> 16.44 23.89 22.77 12.19 19.34 16.16 12.21 22.86 10.42 16.67 18.00 9.24 12.89
#> 145.1 106.1 117 78.2 86.1 41.2 134 29 51 180 57 25 40.2
#> 10.07 16.67 17.46 23.88 23.81 18.02 17.81 15.45 18.23 14.82 14.46 6.32 18.00
#> 170 177.1 51.1 164.1 49.3 113.1 30 32 15 128 143 53 104
#> 19.54 12.53 18.23 23.60 12.19 22.86 17.43 20.90 22.68 20.35 24.00 24.00 24.00
#> 118 191 176 102 9 1 126 173 163 165 112 196 165.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 54 119 116 112.1 144 126.1 144.1 152 152.1 132 148 176.1 120
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 83 131 119.1 193 3 46 19 7 178 112.2 173.1 119.2 72
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20 21 196.1 1.1 162 148.1 98 165.2 152.2 147 46.1 47 160
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67 27 21.1 84 186 162.1 94 147.1 22 148.2 119.3 48 20.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20.2 182 138 2 67.1 161 75 83.1 53.1 138.1 74 186.1 162.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64 38 9.1 2.1 147.2
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[5]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.007930512 0.859431914 0.554291394
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.376485048 0.002839085 0.113999081
#> grade_iii, Cure model
#> 1.315098018
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 63 22.77 1 31 1 0
#> 78 23.88 1 43 0 0
#> 105 19.75 1 60 0 0
#> 78.1 23.88 1 43 0 0
#> 153 21.33 1 55 1 0
#> 43 12.10 1 61 0 1
#> 139 21.49 1 63 1 0
#> 50 10.02 1 NA 1 0
#> 57 14.46 1 45 0 1
#> 113 22.86 1 34 0 0
#> 125 15.65 1 67 1 0
#> 66 22.13 1 53 0 0
#> 55 19.34 1 69 0 1
#> 184 17.77 1 38 0 0
#> 108 18.29 1 39 0 1
#> 60 13.15 1 38 1 0
#> 25 6.32 1 34 1 0
#> 55.1 19.34 1 69 0 1
#> 5 16.43 1 51 0 1
#> 61 10.12 1 36 0 1
#> 188 16.16 1 46 0 1
#> 139.1 21.49 1 63 1 0
#> 88 18.37 1 47 0 0
#> 25.1 6.32 1 34 1 0
#> 49 12.19 1 48 1 0
#> 175 21.91 1 43 0 0
#> 23 16.92 1 61 0 0
#> 154 12.63 1 20 1 0
#> 154.1 12.63 1 20 1 0
#> 124 9.73 1 NA 1 0
#> 55.2 19.34 1 69 0 1
#> 170 19.54 1 43 0 1
#> 24 23.89 1 38 0 0
#> 23.1 16.92 1 61 0 0
#> 134 17.81 1 47 1 0
#> 56 12.21 1 60 0 0
#> 100 16.07 1 60 0 0
#> 133 14.65 1 57 0 0
#> 69 23.23 1 25 0 1
#> 85 16.44 1 36 0 0
#> 14 12.89 1 21 0 0
#> 52 10.42 1 52 0 1
#> 171 16.57 1 41 0 1
#> 55.3 19.34 1 69 0 1
#> 45 17.42 1 54 0 1
#> 52.1 10.42 1 52 0 1
#> 184.1 17.77 1 38 0 0
#> 175.1 21.91 1 43 0 0
#> 5.1 16.43 1 51 0 1
#> 181 16.46 1 45 0 1
#> 13 14.34 1 54 0 1
#> 164 23.60 1 76 0 1
#> 164.1 23.60 1 76 0 1
#> 124.1 9.73 1 NA 1 0
#> 168 23.72 1 70 0 0
#> 164.2 23.60 1 76 0 1
#> 159 10.55 1 50 0 1
#> 8 18.43 1 32 0 0
#> 14.1 12.89 1 21 0 0
#> 155 13.08 1 26 0 0
#> 68 20.62 1 44 0 0
#> 129 23.41 1 53 1 0
#> 128 20.35 1 35 0 1
#> 50.1 10.02 1 NA 1 0
#> 57.1 14.46 1 45 0 1
#> 51 18.23 1 83 0 1
#> 199 19.81 1 NA 0 1
#> 78.2 23.88 1 43 0 0
#> 150 20.33 1 48 0 0
#> 57.2 14.46 1 45 0 1
#> 166 19.98 1 48 0 0
#> 108.1 18.29 1 39 0 1
#> 30 17.43 1 78 0 0
#> 194 22.40 1 38 0 1
#> 99 21.19 1 38 0 1
#> 13.1 14.34 1 54 0 1
#> 4 17.64 1 NA 0 1
#> 130 16.47 1 53 0 1
#> 69.1 23.23 1 25 0 1
#> 81 14.06 1 34 0 0
#> 70 7.38 1 30 1 0
#> 140 12.68 1 59 1 0
#> 99.1 21.19 1 38 0 1
#> 117 17.46 1 26 0 1
#> 57.3 14.46 1 45 0 1
#> 36 21.19 1 48 0 1
#> 150.1 20.33 1 48 0 0
#> 123 13.00 1 44 1 0
#> 145 10.07 1 65 1 0
#> 127 3.53 1 62 0 1
#> 133.1 14.65 1 57 0 0
#> 76 19.22 1 54 0 1
#> 4.1 17.64 1 NA 0 1
#> 190 20.81 1 42 1 0
#> 113.1 22.86 1 34 0 0
#> 140.1 12.68 1 59 1 0
#> 90 20.94 1 50 0 1
#> 189 10.51 1 NA 1 0
#> 8.1 18.43 1 32 0 0
#> 187 9.92 1 39 1 0
#> 24.1 23.89 1 38 0 0
#> 55.4 19.34 1 69 0 1
#> 188.1 16.16 1 46 0 1
#> 194.1 22.40 1 38 0 1
#> 85.1 16.44 1 36 0 0
#> 61.1 10.12 1 36 0 1
#> 68.1 20.62 1 44 0 0
#> 101 9.97 1 10 0 1
#> 43.1 12.10 1 61 0 1
#> 36.1 21.19 1 48 0 1
#> 59 10.16 1 NA 1 0
#> 169 22.41 1 46 0 0
#> 48 24.00 0 31 1 0
#> 71 24.00 0 51 0 0
#> 35 24.00 0 51 0 0
#> 64 24.00 0 43 0 0
#> 196 24.00 0 19 0 0
#> 198 24.00 0 66 0 1
#> 12 24.00 0 63 0 0
#> 21 24.00 0 47 0 0
#> 102 24.00 0 49 0 0
#> 73 24.00 0 NA 0 1
#> 200 24.00 0 64 0 0
#> 172 24.00 0 41 0 0
#> 131 24.00 0 66 0 0
#> 173 24.00 0 19 0 1
#> 160 24.00 0 31 1 0
#> 156 24.00 0 50 1 0
#> 53 24.00 0 32 0 1
#> 115 24.00 0 NA 1 0
#> 21.1 24.00 0 47 0 0
#> 162 24.00 0 51 0 0
#> 151 24.00 0 42 0 0
#> 64.1 24.00 0 43 0 0
#> 132 24.00 0 55 0 0
#> 186 24.00 0 45 1 0
#> 165 24.00 0 47 0 0
#> 196.1 24.00 0 19 0 0
#> 165.1 24.00 0 47 0 0
#> 131.1 24.00 0 66 0 0
#> 160.1 24.00 0 31 1 0
#> 121 24.00 0 57 1 0
#> 185 24.00 0 44 1 0
#> 174 24.00 0 49 1 0
#> 161 24.00 0 45 0 0
#> 132.1 24.00 0 55 0 0
#> 161.1 24.00 0 45 0 0
#> 64.2 24.00 0 43 0 0
#> 109 24.00 0 48 0 0
#> 178 24.00 0 52 1 0
#> 3 24.00 0 31 1 0
#> 131.2 24.00 0 66 0 0
#> 62 24.00 0 71 0 0
#> 193 24.00 0 45 0 1
#> 21.2 24.00 0 47 0 0
#> 53.1 24.00 0 32 0 1
#> 198.1 24.00 0 66 0 1
#> 165.2 24.00 0 47 0 0
#> 142 24.00 0 53 0 0
#> 191 24.00 0 60 0 1
#> 198.2 24.00 0 66 0 1
#> 48.1 24.00 0 31 1 0
#> 176 24.00 0 43 0 1
#> 163 24.00 0 66 0 0
#> 34 24.00 0 36 0 0
#> 48.2 24.00 0 31 1 0
#> 65 24.00 0 57 1 0
#> 138 24.00 0 44 1 0
#> 9 24.00 0 31 1 0
#> 75 24.00 0 21 1 0
#> 156.1 24.00 0 50 1 0
#> 38 24.00 0 31 1 0
#> 12.1 24.00 0 63 0 0
#> 21.3 24.00 0 47 0 0
#> 165.3 24.00 0 47 0 0
#> 73.1 24.00 0 NA 0 1
#> 142.1 24.00 0 53 0 0
#> 126 24.00 0 48 0 0
#> 64.3 24.00 0 43 0 0
#> 119 24.00 0 17 0 0
#> 74 24.00 0 43 0 1
#> 83 24.00 0 6 0 0
#> 34.1 24.00 0 36 0 0
#> 75.1 24.00 0 21 1 0
#> 27 24.00 0 63 1 0
#> 191.1 24.00 0 60 0 1
#> 62.1 24.00 0 71 0 0
#> 62.2 24.00 0 71 0 0
#> 54 24.00 0 53 1 0
#> 191.2 24.00 0 60 0 1
#> 17 24.00 0 38 0 1
#> 102.1 24.00 0 49 0 0
#> 2 24.00 0 9 0 0
#> 174.1 24.00 0 49 1 0
#> 119.1 24.00 0 17 0 0
#> 185.1 24.00 0 44 1 0
#> 163.1 24.00 0 66 0 0
#> 17.1 24.00 0 38 0 1
#> 53.2 24.00 0 32 0 1
#> 116 24.00 0 58 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.376 NA NA NA
#> 2 age, Cure model 0.00284 NA NA NA
#> 3 grade_ii, Cure model 0.114 NA NA NA
#> 4 grade_iii, Cure model 1.32 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00793 NA NA NA
#> 2 grade_ii, Survival model 0.859 NA NA NA
#> 3 grade_iii, Survival model 0.554 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.376485 0.002839 0.113999 1.315098
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 258.9
#> Residual Deviance: 243.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.376485048 0.002839085 0.113999081 1.315098018
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.007930512 0.859431914 0.554291394
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.150539940 0.021630036 0.366839381 0.021630036 0.243689185 0.874311517
#> [7] 0.223428501 0.704419823 0.129041242 0.675290580 0.191834345 0.386453777
#> [13] 0.510392471 0.471765839 0.771096593 0.973875744 0.386453777 0.626949856
#> [19] 0.919951434 0.646308548 0.223428501 0.461924569 0.973875744 0.865109951
#> [25] 0.202341704 0.558721991 0.837498784 0.837498784 0.386453777 0.376676921
#> [31] 0.005597879 0.558721991 0.500766199 0.855847891 0.665547069 0.684979808
#> [37] 0.108362669 0.607494113 0.799757228 0.901760170 0.578214490 0.386453777
#> [43] 0.549020220 0.901760170 0.510392471 0.202341704 0.626949856 0.597765122
#> [49] 0.742313792 0.063011499 0.063011499 0.049623751 0.063011499 0.892589856
#> [55] 0.442578572 0.799757228 0.780661161 0.309681339 0.096462495 0.328560312
#> [61] 0.704419823 0.491022510 0.021630036 0.338051248 0.704419823 0.357100734
#> [67] 0.471765839 0.539295370 0.171761981 0.253812857 0.742313792 0.588001453
#> [73] 0.108362669 0.761442541 0.965011858 0.818732212 0.253812857 0.529650749
#> [79] 0.704419823 0.253812857 0.338051248 0.790247615 0.938032453 0.991269568
#> [85] 0.684979808 0.432893505 0.300265343 0.129041242 0.818732212 0.290640298
#> [91] 0.442578572 0.956077252 0.005597879 0.386453777 0.646308548 0.171761981
#> [97] 0.607494113 0.919951434 0.309681339 0.947080981 0.874311517 0.253812857
#> [103] 0.161044030 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000
#>
#> $Time
#> 63 78 105 78.1 153 43 139 57 113 125 66 55 184
#> 22.77 23.88 19.75 23.88 21.33 12.10 21.49 14.46 22.86 15.65 22.13 19.34 17.77
#> 108 60 25 55.1 5 61 188 139.1 88 25.1 49 175 23
#> 18.29 13.15 6.32 19.34 16.43 10.12 16.16 21.49 18.37 6.32 12.19 21.91 16.92
#> 154 154.1 55.2 170 24 23.1 134 56 100 133 69 85 14
#> 12.63 12.63 19.34 19.54 23.89 16.92 17.81 12.21 16.07 14.65 23.23 16.44 12.89
#> 52 171 55.3 45 52.1 184.1 175.1 5.1 181 13 164 164.1 168
#> 10.42 16.57 19.34 17.42 10.42 17.77 21.91 16.43 16.46 14.34 23.60 23.60 23.72
#> 164.2 159 8 14.1 155 68 129 128 57.1 51 78.2 150 57.2
#> 23.60 10.55 18.43 12.89 13.08 20.62 23.41 20.35 14.46 18.23 23.88 20.33 14.46
#> 166 108.1 30 194 99 13.1 130 69.1 81 70 140 99.1 117
#> 19.98 18.29 17.43 22.40 21.19 14.34 16.47 23.23 14.06 7.38 12.68 21.19 17.46
#> 57.3 36 150.1 123 145 127 133.1 76 190 113.1 140.1 90 8.1
#> 14.46 21.19 20.33 13.00 10.07 3.53 14.65 19.22 20.81 22.86 12.68 20.94 18.43
#> 187 24.1 55.4 188.1 194.1 85.1 61.1 68.1 101 43.1 36.1 169 48
#> 9.92 23.89 19.34 16.16 22.40 16.44 10.12 20.62 9.97 12.10 21.19 22.41 24.00
#> 71 35 64 196 198 12 21 102 200 172 131 173 160
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156 53 21.1 162 151 64.1 132 186 165 196.1 165.1 131.1 160.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 121 185 174 161 132.1 161.1 64.2 109 178 3 131.2 62 193
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 21.2 53.1 198.1 165.2 142 191 198.2 48.1 176 163 34 48.2 65
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 138 9 75 156.1 38 12.1 21.3 165.3 142.1 126 64.3 119 74
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 83 34.1 75.1 27 191.1 62.1 62.2 54 191.2 17 102.1 2 174.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 119.1 185.1 163.1 17.1 53.2 116
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[6]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.008988177 0.008213210 0.052495081
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.76331764 0.02453600 -0.77930342
#> grade_iii, Cure model
#> 0.03783041
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 171 16.57 1 41 0 1
#> 59 10.16 1 NA 1 0
#> 55 19.34 1 69 0 1
#> 60 13.15 1 38 1 0
#> 96 14.54 1 33 0 1
#> 136 21.83 1 43 0 1
#> 101 9.97 1 10 0 1
#> 36 21.19 1 48 0 1
#> 10 10.53 1 34 0 0
#> 50 10.02 1 NA 1 0
#> 155 13.08 1 26 0 0
#> 92 22.92 1 47 0 1
#> 51 18.23 1 83 0 1
#> 32 20.90 1 37 1 0
#> 190 20.81 1 42 1 0
#> 90 20.94 1 50 0 1
#> 159 10.55 1 50 0 1
#> 58 19.34 1 39 0 0
#> 101.1 9.97 1 10 0 1
#> 180 14.82 1 37 0 0
#> 59.1 10.16 1 NA 1 0
#> 113 22.86 1 34 0 0
#> 140 12.68 1 59 1 0
#> 81 14.06 1 34 0 0
#> 97 19.14 1 65 0 1
#> 199 19.81 1 NA 0 1
#> 14 12.89 1 21 0 0
#> 4 17.64 1 NA 0 1
#> 69 23.23 1 25 0 1
#> 56 12.21 1 60 0 0
#> 110 17.56 1 65 0 1
#> 8 18.43 1 32 0 0
#> 123 13.00 1 44 1 0
#> 169 22.41 1 46 0 0
#> 158 20.14 1 74 1 0
#> 10.1 10.53 1 34 0 0
#> 110.1 17.56 1 65 0 1
#> 39 15.59 1 37 0 1
#> 199.1 19.81 1 NA 0 1
#> 66 22.13 1 53 0 0
#> 6 15.64 1 39 0 0
#> 66.1 22.13 1 53 0 0
#> 100 16.07 1 60 0 0
#> 66.2 22.13 1 53 0 0
#> 18 15.21 1 49 1 0
#> 91 5.33 1 61 0 1
#> 150 20.33 1 48 0 0
#> 39.1 15.59 1 37 0 1
#> 85 16.44 1 36 0 0
#> 164 23.60 1 76 0 1
#> 159.1 10.55 1 50 0 1
#> 130 16.47 1 53 0 1
#> 69.1 23.23 1 25 0 1
#> 51.1 18.23 1 83 0 1
#> 86 23.81 1 58 0 1
#> 113.1 22.86 1 34 0 0
#> 150.1 20.33 1 48 0 0
#> 90.1 20.94 1 50 0 1
#> 6.1 15.64 1 39 0 0
#> 96.1 14.54 1 33 0 1
#> 89 11.44 1 NA 0 0
#> 167 15.55 1 56 1 0
#> 26 15.77 1 49 0 1
#> 97.1 19.14 1 65 0 1
#> 195 11.76 1 NA 1 0
#> 136.1 21.83 1 43 0 1
#> 51.2 18.23 1 83 0 1
#> 10.2 10.53 1 34 0 0
#> 90.2 20.94 1 50 0 1
#> 32.1 20.90 1 37 1 0
#> 139 21.49 1 63 1 0
#> 66.3 22.13 1 53 0 0
#> 41 18.02 1 40 1 0
#> 45 17.42 1 54 0 1
#> 81.1 14.06 1 34 0 0
#> 85.1 16.44 1 36 0 0
#> 158.1 20.14 1 74 1 0
#> 129 23.41 1 53 1 0
#> 177 12.53 1 75 0 0
#> 133 14.65 1 57 0 0
#> 130.1 16.47 1 53 0 1
#> 5 16.43 1 51 0 1
#> 100.1 16.07 1 60 0 0
#> 78 23.88 1 43 0 0
#> 187 9.92 1 39 1 0
#> 170 19.54 1 43 0 1
#> 177.1 12.53 1 75 0 0
#> 51.3 18.23 1 83 0 1
#> 57 14.46 1 45 0 1
#> 55.1 19.34 1 69 0 1
#> 128 20.35 1 35 0 1
#> 60.1 13.15 1 38 1 0
#> 129.1 23.41 1 53 1 0
#> 169.1 22.41 1 46 0 0
#> 96.2 14.54 1 33 0 1
#> 179 18.63 1 42 0 0
#> 100.2 16.07 1 60 0 0
#> 188 16.16 1 46 0 1
#> 89.1 11.44 1 NA 0 0
#> 117 17.46 1 26 0 1
#> 153 21.33 1 55 1 0
#> 114 13.68 1 NA 0 0
#> 179.1 18.63 1 42 0 0
#> 188.1 16.16 1 46 0 1
#> 8.1 18.43 1 32 0 0
#> 14.1 12.89 1 21 0 0
#> 192 16.44 1 31 1 0
#> 114.1 13.68 1 NA 0 0
#> 169.2 22.41 1 46 0 0
#> 190.1 20.81 1 42 1 0
#> 58.1 19.34 1 39 0 0
#> 68 20.62 1 44 0 0
#> 20 24.00 0 46 1 0
#> 185 24.00 0 44 1 0
#> 119 24.00 0 17 0 0
#> 38 24.00 0 31 1 0
#> 53 24.00 0 32 0 1
#> 75 24.00 0 21 1 0
#> 122 24.00 0 66 0 0
#> 48 24.00 0 31 1 0
#> 31 24.00 0 36 0 1
#> 173 24.00 0 19 0 1
#> 119.1 24.00 0 17 0 0
#> 144 24.00 0 28 0 1
#> 116 24.00 0 58 0 1
#> 83 24.00 0 6 0 0
#> 35 24.00 0 51 0 0
#> 104 24.00 0 50 1 0
#> 47 24.00 0 38 0 1
#> 9 24.00 0 31 1 0
#> 196 24.00 0 19 0 0
#> 143 24.00 0 51 0 0
#> 64 24.00 0 43 0 0
#> 11 24.00 0 42 0 1
#> 33 24.00 0 53 0 0
#> 191 24.00 0 60 0 1
#> 120 24.00 0 68 0 1
#> 48.1 24.00 0 31 1 0
#> 186 24.00 0 45 1 0
#> 152 24.00 0 36 0 1
#> 102 24.00 0 49 0 0
#> 122.1 24.00 0 66 0 0
#> 75.1 24.00 0 21 1 0
#> 121 24.00 0 57 1 0
#> 186.1 24.00 0 45 1 0
#> 47.1 24.00 0 38 0 1
#> 33.1 24.00 0 53 0 0
#> 173.1 24.00 0 19 0 1
#> 161 24.00 0 45 0 0
#> 200 24.00 0 64 0 0
#> 146 24.00 0 63 1 0
#> 104.1 24.00 0 50 1 0
#> 38.1 24.00 0 31 1 0
#> 156 24.00 0 50 1 0
#> 75.2 24.00 0 21 1 0
#> 80 24.00 0 41 0 0
#> 94 24.00 0 51 0 1
#> 53.1 24.00 0 32 0 1
#> 9.1 24.00 0 31 1 0
#> 109 24.00 0 48 0 0
#> 142 24.00 0 53 0 0
#> 94.1 24.00 0 51 0 1
#> 75.3 24.00 0 21 1 0
#> 11.1 24.00 0 42 0 1
#> 54 24.00 0 53 1 0
#> 135 24.00 0 58 1 0
#> 116.1 24.00 0 58 0 1
#> 193 24.00 0 45 0 1
#> 67 24.00 0 25 0 0
#> 72 24.00 0 40 0 1
#> 146.1 24.00 0 63 1 0
#> 47.2 24.00 0 38 0 1
#> 1 24.00 0 23 1 0
#> 72.1 24.00 0 40 0 1
#> 67.1 24.00 0 25 0 0
#> 1.1 24.00 0 23 1 0
#> 132 24.00 0 55 0 0
#> 75.4 24.00 0 21 1 0
#> 126 24.00 0 48 0 0
#> 67.2 24.00 0 25 0 0
#> 109.1 24.00 0 48 0 0
#> 74 24.00 0 43 0 1
#> 135.1 24.00 0 58 1 0
#> 72.2 24.00 0 40 0 1
#> 54.1 24.00 0 53 1 0
#> 200.1 24.00 0 64 0 0
#> 173.2 24.00 0 19 0 1
#> 46 24.00 0 71 0 0
#> 72.3 24.00 0 40 0 1
#> 67.3 24.00 0 25 0 0
#> 72.4 24.00 0 40 0 1
#> 19 24.00 0 57 0 1
#> 152.1 24.00 0 36 0 1
#> 33.2 24.00 0 53 0 0
#> 138 24.00 0 44 1 0
#> 20.1 24.00 0 46 1 0
#> 82 24.00 0 34 0 0
#> 193.1 24.00 0 45 0 1
#> 121.1 24.00 0 57 1 0
#> 165 24.00 0 47 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.763 NA NA NA
#> 2 age, Cure model 0.0245 NA NA NA
#> 3 grade_ii, Cure model -0.779 NA NA NA
#> 4 grade_iii, Cure model 0.0378 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00899 NA NA NA
#> 2 grade_ii, Survival model 0.00821 NA NA NA
#> 3 grade_iii, Survival model 0.0525 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.76332 0.02454 -0.77930 0.03783
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 261.1
#> Residual Deviance: 249.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.76331764 0.02453600 -0.77930342 0.03783041
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.008988177 0.008213210 0.052495081
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.4055426219 0.2175248278 0.7355347976 0.6573736165 0.0742134134
#> [6] 0.9424605716 0.1003441357 0.8999945557 0.7621859203 0.0233052628
#> [11] 0.3106511209 0.1285013780 0.1434510138 0.1074029721 0.8718096552
#> [16] 0.2175248278 0.9424605716 0.6315622563 0.0279856262 0.8163137420
#> [21] 0.7091547049 0.2528334822 0.7892491939 0.0153280885 0.8577515795
#> [26] 0.3618459399 0.2910206080 0.7756796575 0.0373368061 0.1915257587
#> [31] 0.8999945557 0.3618459399 0.5811841900 0.0522606187 0.5565329030
#> [36] 0.0522606187 0.5084065318 0.0522606187 0.6187819823 0.9854683645
#> [41] 0.1750944186 0.5811841900 0.4392335308 0.0046559796 0.8718096552
#> [46] 0.4167357625 0.0153280885 0.3106511209 0.0021640313 0.0279856262
#> [51] 0.1750944186 0.1074029721 0.5565329030 0.6573736165 0.6060936789
#> [56] 0.5442306972 0.2528334822 0.0742134134 0.3106511209 0.8999945557
#> [61] 0.1074029721 0.1285013780 0.0867243480 0.0522606187 0.3511544999
#> [66] 0.3944325816 0.7091547049 0.4392335308 0.1915257587 0.0080235901
#> [71] 0.8300535010 0.6444161262 0.4167357625 0.4732238846 0.5084065318
#> [76] 0.0004966671 0.9710200157 0.2086656899 0.8300535010 0.3106511209
#> [81] 0.6959700809 0.2175248278 0.1669512935 0.7355347976 0.0080235901
#> [86] 0.0373368061 0.6573736165 0.2717159451 0.5084065318 0.4849325135
#> [91] 0.3834314285 0.0934386526 0.2717159451 0.4849325135 0.2910206080
#> [96] 0.7892491939 0.4392335308 0.0373368061 0.1434510138 0.2175248278
#> [101] 0.1588987831 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#>
#> $Time
#> 171 55 60 96 136 101 36 10 155 92 51 32 190
#> 16.57 19.34 13.15 14.54 21.83 9.97 21.19 10.53 13.08 22.92 18.23 20.90 20.81
#> 90 159 58 101.1 180 113 140 81 97 14 69 56 110
#> 20.94 10.55 19.34 9.97 14.82 22.86 12.68 14.06 19.14 12.89 23.23 12.21 17.56
#> 8 123 169 158 10.1 110.1 39 66 6 66.1 100 66.2 18
#> 18.43 13.00 22.41 20.14 10.53 17.56 15.59 22.13 15.64 22.13 16.07 22.13 15.21
#> 91 150 39.1 85 164 159.1 130 69.1 51.1 86 113.1 150.1 90.1
#> 5.33 20.33 15.59 16.44 23.60 10.55 16.47 23.23 18.23 23.81 22.86 20.33 20.94
#> 6.1 96.1 167 26 97.1 136.1 51.2 10.2 90.2 32.1 139 66.3 41
#> 15.64 14.54 15.55 15.77 19.14 21.83 18.23 10.53 20.94 20.90 21.49 22.13 18.02
#> 45 81.1 85.1 158.1 129 177 133 130.1 5 100.1 78 187 170
#> 17.42 14.06 16.44 20.14 23.41 12.53 14.65 16.47 16.43 16.07 23.88 9.92 19.54
#> 177.1 51.3 57 55.1 128 60.1 129.1 169.1 96.2 179 100.2 188 117
#> 12.53 18.23 14.46 19.34 20.35 13.15 23.41 22.41 14.54 18.63 16.07 16.16 17.46
#> 153 179.1 188.1 8.1 14.1 192 169.2 190.1 58.1 68 20 185 119
#> 21.33 18.63 16.16 18.43 12.89 16.44 22.41 20.81 19.34 20.62 24.00 24.00 24.00
#> 38 53 75 122 48 31 173 119.1 144 116 83 35 104
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 47 9 196 143 64 11 33 191 120 48.1 186 152 102
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 122.1 75.1 121 186.1 47.1 33.1 173.1 161 200 146 104.1 38.1 156
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75.2 80 94 53.1 9.1 109 142 94.1 75.3 11.1 54 135 116.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193 67 72 146.1 47.2 1 72.1 67.1 1.1 132 75.4 126 67.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 109.1 74 135.1 72.2 54.1 200.1 173.2 46 72.3 67.3 72.4 19 152.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33.2 138 20.1 82 193.1 121.1 165
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[7]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.005080075 0.582521195 0.153194443
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.28222261 0.02401492 0.19518324
#> grade_iii, Cure model
#> 0.76122484
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 150 20.33 1 48 0 0
#> 180 14.82 1 37 0 0
#> 77 7.27 1 67 0 1
#> 136 21.83 1 43 0 1
#> 68 20.62 1 44 0 0
#> 42 12.43 1 49 0 1
#> 167 15.55 1 56 1 0
#> 194 22.40 1 38 0 1
#> 57 14.46 1 45 0 1
#> 4 17.64 1 NA 0 1
#> 93 10.33 1 52 0 1
#> 81 14.06 1 34 0 0
#> 125 15.65 1 67 1 0
#> 158 20.14 1 74 1 0
#> 5 16.43 1 51 0 1
#> 183 9.24 1 67 1 0
#> 199 19.81 1 NA 0 1
#> 41 18.02 1 40 1 0
#> 16 8.71 1 71 0 1
#> 56 12.21 1 60 0 0
#> 181 16.46 1 45 0 1
#> 139 21.49 1 63 1 0
#> 140 12.68 1 59 1 0
#> 58 19.34 1 39 0 0
#> 153 21.33 1 55 1 0
#> 23 16.92 1 61 0 0
#> 24 23.89 1 38 0 0
#> 159 10.55 1 50 0 1
#> 136.1 21.83 1 43 0 1
#> 4.1 17.64 1 NA 0 1
#> 30 17.43 1 78 0 0
#> 37 12.52 1 57 1 0
#> 13 14.34 1 54 0 1
#> 123 13.00 1 44 1 0
#> 4.2 17.64 1 NA 0 1
#> 189 10.51 1 NA 1 0
#> 81.1 14.06 1 34 0 0
#> 42.1 12.43 1 49 0 1
#> 96 14.54 1 33 0 1
#> 127 3.53 1 62 0 1
#> 128 20.35 1 35 0 1
#> 100 16.07 1 60 0 0
#> 106 16.67 1 49 1 0
#> 166 19.98 1 48 0 0
#> 150.1 20.33 1 48 0 0
#> 45 17.42 1 54 0 1
#> 30.1 17.43 1 78 0 0
#> 55 19.34 1 69 0 1
#> 59 10.16 1 NA 1 0
#> 55.1 19.34 1 69 0 1
#> 41.1 18.02 1 40 1 0
#> 77.1 7.27 1 67 0 1
#> 23.1 16.92 1 61 0 0
#> 133 14.65 1 57 0 0
#> 88 18.37 1 47 0 0
#> 43 12.10 1 61 0 1
#> 123.1 13.00 1 44 1 0
#> 79 16.23 1 54 1 0
#> 42.2 12.43 1 49 0 1
#> 15 22.68 1 48 0 0
#> 69 23.23 1 25 0 1
#> 124 9.73 1 NA 1 0
#> 107 11.18 1 54 1 0
#> 69.1 23.23 1 25 0 1
#> 199.1 19.81 1 NA 0 1
#> 177 12.53 1 75 0 0
#> 164 23.60 1 76 0 1
#> 6 15.64 1 39 0 0
#> 124.1 9.73 1 NA 1 0
#> 70 7.38 1 30 1 0
#> 45.1 17.42 1 54 0 1
#> 69.2 23.23 1 25 0 1
#> 81.2 14.06 1 34 0 0
#> 199.2 19.81 1 NA 0 1
#> 49 12.19 1 48 1 0
#> 85 16.44 1 36 0 0
#> 158.1 20.14 1 74 1 0
#> 66 22.13 1 53 0 0
#> 49.1 12.19 1 48 1 0
#> 183.1 9.24 1 67 1 0
#> 89 11.44 1 NA 0 0
#> 123.2 13.00 1 44 1 0
#> 183.2 9.24 1 67 1 0
#> 76 19.22 1 54 0 1
#> 63 22.77 1 31 1 0
#> 155 13.08 1 26 0 0
#> 91 5.33 1 61 0 1
#> 10 10.53 1 34 0 0
#> 60 13.15 1 38 1 0
#> 13.1 14.34 1 54 0 1
#> 68.1 20.62 1 44 0 0
#> 25 6.32 1 34 1 0
#> 49.2 12.19 1 48 1 0
#> 8 18.43 1 32 0 0
#> 194.1 22.40 1 38 0 1
#> 79.1 16.23 1 54 1 0
#> 179 18.63 1 42 0 0
#> 18 15.21 1 49 1 0
#> 49.3 12.19 1 48 1 0
#> 43.1 12.10 1 61 0 1
#> 158.2 20.14 1 74 1 0
#> 55.2 19.34 1 69 0 1
#> 175 21.91 1 43 0 0
#> 149 8.37 1 33 1 0
#> 55.3 19.34 1 69 0 1
#> 111 17.45 1 47 0 1
#> 168 23.72 1 70 0 0
#> 157 15.10 1 47 0 0
#> 4.3 17.64 1 NA 0 1
#> 158.3 20.14 1 74 1 0
#> 133.1 14.65 1 57 0 0
#> 175.1 21.91 1 43 0 0
#> 64 24.00 0 43 0 0
#> 126 24.00 0 48 0 0
#> 115 24.00 0 NA 1 0
#> 191 24.00 0 60 0 1
#> 19 24.00 0 57 0 1
#> 53 24.00 0 32 0 1
#> 193 24.00 0 45 0 1
#> 3 24.00 0 31 1 0
#> 9 24.00 0 31 1 0
#> 121 24.00 0 57 1 0
#> 35 24.00 0 51 0 0
#> 65 24.00 0 57 1 0
#> 109 24.00 0 48 0 0
#> 156 24.00 0 50 1 0
#> 178 24.00 0 52 1 0
#> 196 24.00 0 19 0 0
#> 109.1 24.00 0 48 0 0
#> 161 24.00 0 45 0 0
#> 161.1 24.00 0 45 0 0
#> 75 24.00 0 21 1 0
#> 176 24.00 0 43 0 1
#> 44 24.00 0 56 0 0
#> 65.1 24.00 0 57 1 0
#> 172 24.00 0 41 0 0
#> 165 24.00 0 47 0 0
#> 193.1 24.00 0 45 0 1
#> 94 24.00 0 51 0 1
#> 35.1 24.00 0 51 0 0
#> 53.1 24.00 0 32 0 1
#> 80 24.00 0 41 0 0
#> 84 24.00 0 39 0 1
#> 109.2 24.00 0 48 0 0
#> 172.1 24.00 0 41 0 0
#> 137 24.00 0 45 1 0
#> 138 24.00 0 44 1 0
#> 48 24.00 0 31 1 0
#> 138.1 24.00 0 44 1 0
#> 7 24.00 0 37 1 0
#> 146 24.00 0 63 1 0
#> 104 24.00 0 50 1 0
#> 118 24.00 0 44 1 0
#> 162 24.00 0 51 0 0
#> 165.1 24.00 0 47 0 0
#> 2 24.00 0 9 0 0
#> 103 24.00 0 56 1 0
#> 193.2 24.00 0 45 0 1
#> 112 24.00 0 61 0 0
#> 144 24.00 0 28 0 1
#> 116 24.00 0 58 0 1
#> 21 24.00 0 47 0 0
#> 65.2 24.00 0 57 1 0
#> 126.1 24.00 0 48 0 0
#> 112.1 24.00 0 61 0 0
#> 163 24.00 0 66 0 0
#> 62 24.00 0 71 0 0
#> 176.1 24.00 0 43 0 1
#> 193.3 24.00 0 45 0 1
#> 83 24.00 0 6 0 0
#> 33 24.00 0 53 0 0
#> 161.2 24.00 0 45 0 0
#> 115.1 24.00 0 NA 1 0
#> 148 24.00 0 61 1 0
#> 31 24.00 0 36 0 1
#> 143 24.00 0 51 0 0
#> 185 24.00 0 44 1 0
#> 137.1 24.00 0 45 1 0
#> 74 24.00 0 43 0 1
#> 120 24.00 0 68 0 1
#> 146.1 24.00 0 63 1 0
#> 182 24.00 0 35 0 0
#> 2.1 24.00 0 9 0 0
#> 121.1 24.00 0 57 1 0
#> 119 24.00 0 17 0 0
#> 65.3 24.00 0 57 1 0
#> 7.1 24.00 0 37 1 0
#> 172.2 24.00 0 41 0 0
#> 44.1 24.00 0 56 0 0
#> 115.2 24.00 0 NA 1 0
#> 112.2 24.00 0 61 0 0
#> 21.1 24.00 0 47 0 0
#> 80.1 24.00 0 41 0 0
#> 172.3 24.00 0 41 0 0
#> 165.2 24.00 0 47 0 0
#> 156.1 24.00 0 50 1 0
#> 109.3 24.00 0 48 0 0
#> 147 24.00 0 76 1 0
#> 103.1 24.00 0 56 1 0
#> 95 24.00 0 68 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.28 NA NA NA
#> 2 age, Cure model 0.0240 NA NA NA
#> 3 grade_ii, Cure model 0.195 NA NA NA
#> 4 grade_iii, Cure model 0.761 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00508 NA NA NA
#> 2 grade_ii, Survival model 0.583 NA NA NA
#> 3 grade_iii, Survival model 0.153 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.28222 0.02401 0.19518 0.76122
#>
#> Degrees of Freedom: 184 Total (i.e. Null); 181 Residual
#> Null Deviance: 255.2
#> Residual Deviance: 245.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.28222261 0.02401492 0.19518324 0.76122484
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.005080075 0.582521195 0.153194443
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.38283959 0.71491757 0.97057419 0.28984669 0.34522258 0.84432778
#> [7] 0.69209915 0.21258379 0.74480973 0.92811613 0.76685144 0.67646974
#> [13] 0.40713804 0.64433066 0.93438716 0.54090288 0.95252420 0.86430922
#> [19] 0.62765096 0.31849099 0.82376434 0.45711903 0.33222414 0.60225973
#> [25] 0.02950758 0.91552191 0.28984669 0.56765838 0.83753384 0.75223242
#> [31] 0.80299899 0.76685144 0.84432778 0.73735248 0.99415256 0.37026755
#> [37] 0.66850555 0.61924816 0.44689489 0.38283959 0.58509547 0.56765838
#> [43] 0.45711903 0.45711903 0.54090288 0.97057419 0.60225973 0.72245672
#> [49] 0.53153910 0.89647726 0.80299899 0.65260496 0.84432778 0.19516479
#> [55] 0.12365793 0.90919888 0.12365793 0.83066232 0.09828632 0.68429422
#> [61] 0.96459865 0.58509547 0.12365793 0.76685144 0.87100317 0.63600178
#> [67] 0.40713804 0.24396744 0.87100317 0.93438716 0.80299899 0.93438716
#> [73] 0.50321213 0.17730704 0.79578347 0.98828451 0.92182308 0.78855869
#> [79] 0.75223242 0.34522258 0.98239587 0.87100317 0.52213062 0.21258379
#> [85] 0.65260496 0.51269213 0.69978450 0.87100317 0.89647726 0.40713804
#> [91] 0.45711903 0.25987277 0.95858267 0.45711903 0.55873759 0.06729554
#> [97] 0.70736195 0.40713804 0.72245672 0.25987277 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 150 180 77 136 68 42 167 194 57 93 81 125 158
#> 20.33 14.82 7.27 21.83 20.62 12.43 15.55 22.40 14.46 10.33 14.06 15.65 20.14
#> 5 183 41 16 56 181 139 140 58 153 23 24 159
#> 16.43 9.24 18.02 8.71 12.21 16.46 21.49 12.68 19.34 21.33 16.92 23.89 10.55
#> 136.1 30 37 13 123 81.1 42.1 96 127 128 100 106 166
#> 21.83 17.43 12.52 14.34 13.00 14.06 12.43 14.54 3.53 20.35 16.07 16.67 19.98
#> 150.1 45 30.1 55 55.1 41.1 77.1 23.1 133 88 43 123.1 79
#> 20.33 17.42 17.43 19.34 19.34 18.02 7.27 16.92 14.65 18.37 12.10 13.00 16.23
#> 42.2 15 69 107 69.1 177 164 6 70 45.1 69.2 81.2 49
#> 12.43 22.68 23.23 11.18 23.23 12.53 23.60 15.64 7.38 17.42 23.23 14.06 12.19
#> 85 158.1 66 49.1 183.1 123.2 183.2 76 63 155 91 10 60
#> 16.44 20.14 22.13 12.19 9.24 13.00 9.24 19.22 22.77 13.08 5.33 10.53 13.15
#> 13.1 68.1 25 49.2 8 194.1 79.1 179 18 49.3 43.1 158.2 55.2
#> 14.34 20.62 6.32 12.19 18.43 22.40 16.23 18.63 15.21 12.19 12.10 20.14 19.34
#> 175 149 55.3 111 168 157 158.3 133.1 175.1 64 126 191 19
#> 21.91 8.37 19.34 17.45 23.72 15.10 20.14 14.65 21.91 24.00 24.00 24.00 24.00
#> 53 193 3 9 121 35 65 109 156 178 196 109.1 161
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 161.1 75 176 44 65.1 172 165 193.1 94 35.1 53.1 80 84
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 109.2 172.1 137 138 48 138.1 7 146 104 118 162 165.1 2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103 193.2 112 144 116 21 65.2 126.1 112.1 163 62 176.1 193.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 83 33 161.2 148 31 143 185 137.1 74 120 146.1 182 2.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 121.1 119 65.3 7.1 172.2 44.1 112.2 21.1 80.1 172.3 165.2 156.1 109.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 147 103.1 95
#> 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[8]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.003822368 0.219665174 -0.169378206
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.659284547 0.004892301 0.678153928
#> grade_iii, Cure model
#> 1.177448869
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 96 14.54 1 33 0 1
#> 92 22.92 1 47 0 1
#> 76 19.22 1 54 0 1
#> 49 12.19 1 48 1 0
#> 128 20.35 1 35 0 1
#> 23 16.92 1 61 0 0
#> 114 13.68 1 NA 0 0
#> 159 10.55 1 50 0 1
#> 128.1 20.35 1 35 0 1
#> 69 23.23 1 25 0 1
#> 145 10.07 1 65 1 0
#> 59 10.16 1 NA 1 0
#> 90 20.94 1 50 0 1
#> 123 13.00 1 44 1 0
#> 88 18.37 1 47 0 0
#> 192 16.44 1 31 1 0
#> 86 23.81 1 58 0 1
#> 52 10.42 1 52 0 1
#> 81 14.06 1 34 0 0
#> 183 9.24 1 67 1 0
#> 106 16.67 1 49 1 0
#> 117 17.46 1 26 0 1
#> 195 11.76 1 NA 1 0
#> 136 21.83 1 43 0 1
#> 169 22.41 1 46 0 0
#> 23.1 16.92 1 61 0 0
#> 36 21.19 1 48 0 1
#> 153 21.33 1 55 1 0
#> 13 14.34 1 54 0 1
#> 153.1 21.33 1 55 1 0
#> 36.1 21.19 1 48 0 1
#> 32 20.90 1 37 1 0
#> 8 18.43 1 32 0 0
#> 61 10.12 1 36 0 1
#> 81.1 14.06 1 34 0 0
#> 92.1 22.92 1 47 0 1
#> 133 14.65 1 57 0 0
#> 150 20.33 1 48 0 0
#> 97 19.14 1 65 0 1
#> 89 11.44 1 NA 0 0
#> 40 18.00 1 28 1 0
#> 180 14.82 1 37 0 0
#> 159.1 10.55 1 50 0 1
#> 89.1 11.44 1 NA 0 0
#> 197 21.60 1 69 1 0
#> 56 12.21 1 60 0 0
#> 100 16.07 1 60 0 0
#> 89.2 11.44 1 NA 0 0
#> 30 17.43 1 78 0 0
#> 68 20.62 1 44 0 0
#> 117.1 17.46 1 26 0 1
#> 51 18.23 1 83 0 1
#> 190 20.81 1 42 1 0
#> 192.1 16.44 1 31 1 0
#> 88.1 18.37 1 47 0 0
#> 16 8.71 1 71 0 1
#> 32.1 20.90 1 37 1 0
#> 197.1 21.60 1 69 1 0
#> 154 12.63 1 20 1 0
#> 188 16.16 1 46 0 1
#> 157 15.10 1 47 0 0
#> 16.1 8.71 1 71 0 1
#> 32.2 20.90 1 37 1 0
#> 92.2 22.92 1 47 0 1
#> 124 9.73 1 NA 1 0
#> 184 17.77 1 38 0 0
#> 107 11.18 1 54 1 0
#> 5 16.43 1 51 0 1
#> 189 10.51 1 NA 1 0
#> 154.1 12.63 1 20 1 0
#> 125 15.65 1 67 1 0
#> 77 7.27 1 67 0 1
#> 108 18.29 1 39 0 1
#> 187 9.92 1 39 1 0
#> 184.1 17.77 1 38 0 0
#> 26 15.77 1 49 0 1
#> 30.1 17.43 1 78 0 0
#> 171 16.57 1 41 0 1
#> 166 19.98 1 48 0 0
#> 101 9.97 1 10 0 1
#> 113 22.86 1 34 0 0
#> 149 8.37 1 33 1 0
#> 13.1 14.34 1 54 0 1
#> 154.2 12.63 1 20 1 0
#> 58 19.34 1 39 0 0
#> 56.1 12.21 1 60 0 0
#> 18 15.21 1 49 1 0
#> 106.1 16.67 1 49 1 0
#> 167 15.55 1 56 1 0
#> 140 12.68 1 59 1 0
#> 166.1 19.98 1 48 0 0
#> 76.1 19.22 1 54 0 1
#> 15 22.68 1 48 0 0
#> 113.1 22.86 1 34 0 0
#> 145.1 10.07 1 65 1 0
#> 189.1 10.51 1 NA 1 0
#> 32.3 20.90 1 37 1 0
#> 37 12.52 1 57 1 0
#> 99 21.19 1 38 0 1
#> 76.2 19.22 1 54 0 1
#> 192.2 16.44 1 31 1 0
#> 18.1 15.21 1 49 1 0
#> 129 23.41 1 53 1 0
#> 51.1 18.23 1 83 0 1
#> 101.1 9.97 1 10 0 1
#> 96.1 14.54 1 33 0 1
#> 25 6.32 1 34 1 0
#> 139 21.49 1 63 1 0
#> 167.1 15.55 1 56 1 0
#> 189.2 10.51 1 NA 1 0
#> 111 17.45 1 47 0 1
#> 86.1 23.81 1 58 0 1
#> 64 24.00 0 43 0 0
#> 162 24.00 0 51 0 0
#> 161 24.00 0 45 0 0
#> 47 24.00 0 38 0 1
#> 74 24.00 0 43 0 1
#> 142 24.00 0 53 0 0
#> 160 24.00 0 31 1 0
#> 174 24.00 0 49 1 0
#> 165 24.00 0 47 0 0
#> 144 24.00 0 28 0 1
#> 165.1 24.00 0 47 0 0
#> 191 24.00 0 60 0 1
#> 94 24.00 0 51 0 1
#> 148 24.00 0 61 1 0
#> 200 24.00 0 64 0 0
#> 118 24.00 0 44 1 0
#> 44 24.00 0 56 0 0
#> 165.2 24.00 0 47 0 0
#> 185 24.00 0 44 1 0
#> 65 24.00 0 57 1 0
#> 119 24.00 0 17 0 0
#> 176 24.00 0 43 0 1
#> 142.1 24.00 0 53 0 0
#> 84 24.00 0 39 0 1
#> 119.1 24.00 0 17 0 0
#> 161.1 24.00 0 45 0 0
#> 165.3 24.00 0 47 0 0
#> 165.4 24.00 0 47 0 0
#> 74.1 24.00 0 43 0 1
#> 121 24.00 0 57 1 0
#> 151 24.00 0 42 0 0
#> 38 24.00 0 31 1 0
#> 103 24.00 0 56 1 0
#> 193 24.00 0 45 0 1
#> 135 24.00 0 58 1 0
#> 165.5 24.00 0 47 0 0
#> 104 24.00 0 50 1 0
#> 28 24.00 0 67 1 0
#> 148.1 24.00 0 61 1 0
#> 119.2 24.00 0 17 0 0
#> 174.1 24.00 0 49 1 0
#> 94.1 24.00 0 51 0 1
#> 27 24.00 0 63 1 0
#> 126 24.00 0 48 0 0
#> 47.1 24.00 0 38 0 1
#> 132 24.00 0 55 0 0
#> 94.2 24.00 0 51 0 1
#> 12 24.00 0 63 0 0
#> 74.2 24.00 0 43 0 1
#> 12.1 24.00 0 63 0 0
#> 104.1 24.00 0 50 1 0
#> 143 24.00 0 51 0 0
#> 35 24.00 0 51 0 0
#> 17 24.00 0 38 0 1
#> 62 24.00 0 71 0 0
#> 7 24.00 0 37 1 0
#> 73 24.00 0 NA 0 1
#> 142.2 24.00 0 53 0 0
#> 161.2 24.00 0 45 0 0
#> 7.1 24.00 0 37 1 0
#> 74.3 24.00 0 43 0 1
#> 62.1 24.00 0 71 0 0
#> 7.2 24.00 0 37 1 0
#> 196 24.00 0 19 0 0
#> 84.1 24.00 0 39 0 1
#> 126.1 24.00 0 48 0 0
#> 151.1 24.00 0 42 0 0
#> 54 24.00 0 53 1 0
#> 48 24.00 0 31 1 0
#> 87 24.00 0 27 0 0
#> 120 24.00 0 68 0 1
#> 22 24.00 0 52 1 0
#> 119.3 24.00 0 17 0 0
#> 119.4 24.00 0 17 0 0
#> 186 24.00 0 45 1 0
#> 162.1 24.00 0 51 0 0
#> 121.1 24.00 0 57 1 0
#> 20 24.00 0 46 1 0
#> 102 24.00 0 49 0 0
#> 27.1 24.00 0 63 1 0
#> 48.1 24.00 0 31 1 0
#> 22.1 24.00 0 52 1 0
#> 12.2 24.00 0 63 0 0
#> 82 24.00 0 34 0 0
#> 84.2 24.00 0 39 0 1
#> 109 24.00 0 48 0 0
#> 94.3 24.00 0 51 0 1
#> 21 24.00 0 47 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.659 NA NA NA
#> 2 age, Cure model 0.00489 NA NA NA
#> 3 grade_ii, Cure model 0.678 NA NA NA
#> 4 grade_iii, Cure model 1.18 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00382 NA NA NA
#> 2 grade_ii, Survival model 0.220 NA NA NA
#> 3 grade_iii, Survival model -0.169 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.659285 0.004892 0.678154 1.177449
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.8
#> Residual Deviance: 250.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.659284547 0.004892301 0.678153928 1.177448869
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.003822368 0.219665174 -0.169378206
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.656725927 0.025580976 0.267104603 0.809706830 0.212647629 0.444975918
#> [7] 0.831767074 0.212647629 0.018598615 0.876215843 0.152595659 0.722227957
#> [13] 0.314354157 0.497336659 0.002780291 0.853855242 0.700265206 0.932109940
#> [19] 0.465867311 0.393665988 0.076781891 0.068427178 0.444975918 0.127148477
#> [25] 0.110562424 0.678386131 0.110562424 0.127148477 0.161762600 0.304626306
#> [31] 0.865016443 0.700265206 0.025580976 0.645897197 0.230469674 0.294934112
#> [37] 0.363549490 0.635103896 0.831767074 0.085403493 0.787783965 0.549519693
#> [43] 0.424286683 0.203741529 0.393665988 0.343601331 0.194895342 0.497336659
#> [49] 0.314354157 0.943361416 0.161762600 0.085403493 0.744343350 0.538870630
#> [55] 0.624334736 0.943361416 0.161762600 0.025580976 0.373630856 0.820737940
#> [61] 0.528282653 0.744343350 0.570964326 0.977254182 0.333703005 0.920863322
#> [67] 0.373630856 0.560211224 0.424286683 0.486728090 0.239620510 0.898487581
#> [73] 0.045282624 0.965920866 0.678386131 0.744343350 0.257801585 0.787783965
#> [79] 0.603042051 0.465867311 0.581724683 0.733285165 0.239620510 0.267104603
#> [85] 0.060234773 0.045282624 0.876215843 0.161762600 0.776808251 0.127148477
#> [91] 0.267104603 0.497336659 0.603042051 0.012196214 0.343601331 0.898487581
#> [97] 0.656725927 0.988633229 0.101922377 0.581724683 0.413944519 0.002780291
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 96 92 76 49 128 23 159 128.1 69 145 90 123 88
#> 14.54 22.92 19.22 12.19 20.35 16.92 10.55 20.35 23.23 10.07 20.94 13.00 18.37
#> 192 86 52 81 183 106 117 136 169 23.1 36 153 13
#> 16.44 23.81 10.42 14.06 9.24 16.67 17.46 21.83 22.41 16.92 21.19 21.33 14.34
#> 153.1 36.1 32 8 61 81.1 92.1 133 150 97 40 180 159.1
#> 21.33 21.19 20.90 18.43 10.12 14.06 22.92 14.65 20.33 19.14 18.00 14.82 10.55
#> 197 56 100 30 68 117.1 51 190 192.1 88.1 16 32.1 197.1
#> 21.60 12.21 16.07 17.43 20.62 17.46 18.23 20.81 16.44 18.37 8.71 20.90 21.60
#> 154 188 157 16.1 32.2 92.2 184 107 5 154.1 125 77 108
#> 12.63 16.16 15.10 8.71 20.90 22.92 17.77 11.18 16.43 12.63 15.65 7.27 18.29
#> 187 184.1 26 30.1 171 166 101 113 149 13.1 154.2 58 56.1
#> 9.92 17.77 15.77 17.43 16.57 19.98 9.97 22.86 8.37 14.34 12.63 19.34 12.21
#> 18 106.1 167 140 166.1 76.1 15 113.1 145.1 32.3 37 99 76.2
#> 15.21 16.67 15.55 12.68 19.98 19.22 22.68 22.86 10.07 20.90 12.52 21.19 19.22
#> 192.2 18.1 129 51.1 101.1 96.1 25 139 167.1 111 86.1 64 162
#> 16.44 15.21 23.41 18.23 9.97 14.54 6.32 21.49 15.55 17.45 23.81 24.00 24.00
#> 161 47 74 142 160 174 165 144 165.1 191 94 148 200
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 118 44 165.2 185 65 119 176 142.1 84 119.1 161.1 165.3 165.4
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 74.1 121 151 38 103 193 135 165.5 104 28 148.1 119.2 174.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94.1 27 126 47.1 132 94.2 12 74.2 12.1 104.1 143 35 17
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62 7 142.2 161.2 7.1 74.3 62.1 7.2 196 84.1 126.1 151.1 54
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 48 87 120 22 119.3 119.4 186 162.1 121.1 20 102 27.1 48.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 22.1 12.2 82 84.2 109 94.3 21
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[9]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.004737585 0.111644228 -0.004107459
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.15141376 0.01803268 0.77044904
#> grade_iii, Cure model
#> 0.70475844
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 90 20.94 1 50 0 1
#> 123 13.00 1 44 1 0
#> 177 12.53 1 75 0 0
#> 85 16.44 1 36 0 0
#> 40 18.00 1 28 1 0
#> 171 16.57 1 41 0 1
#> 58 19.34 1 39 0 0
#> 29 15.45 1 68 1 0
#> 129 23.41 1 53 1 0
#> 93 10.33 1 52 0 1
#> 99 21.19 1 38 0 1
#> 159 10.55 1 50 0 1
#> 139 21.49 1 63 1 0
#> 25 6.32 1 34 1 0
#> 107 11.18 1 54 1 0
#> 93.1 10.33 1 52 0 1
#> 86 23.81 1 58 0 1
#> 192 16.44 1 31 1 0
#> 77 7.27 1 67 0 1
#> 107.1 11.18 1 54 1 0
#> 10 10.53 1 34 0 0
#> 133 14.65 1 57 0 0
#> 168 23.72 1 70 0 0
#> 100 16.07 1 60 0 0
#> 56 12.21 1 60 0 0
#> 183 9.24 1 67 1 0
#> 36 21.19 1 48 0 1
#> 10.1 10.53 1 34 0 0
#> 50 10.02 1 NA 1 0
#> 42 12.43 1 49 0 1
#> 26 15.77 1 49 0 1
#> 76 19.22 1 54 0 1
#> 129.1 23.41 1 53 1 0
#> 43 12.10 1 61 0 1
#> 88 18.37 1 47 0 0
#> 101 9.97 1 10 0 1
#> 92 22.92 1 47 0 1
#> 167 15.55 1 56 1 0
#> 77.1 7.27 1 67 0 1
#> 13 14.34 1 54 0 1
#> 63 22.77 1 31 1 0
#> 153 21.33 1 55 1 0
#> 42.1 12.43 1 49 0 1
#> 164 23.60 1 76 0 1
#> 105 19.75 1 60 0 0
#> 159.1 10.55 1 50 0 1
#> 76.1 19.22 1 54 0 1
#> 158 20.14 1 74 1 0
#> 43.1 12.10 1 61 0 1
#> 29.1 15.45 1 68 1 0
#> 63.1 22.77 1 31 1 0
#> 107.2 11.18 1 54 1 0
#> 36.1 21.19 1 48 0 1
#> 70 7.38 1 30 1 0
#> 170 19.54 1 43 0 1
#> 188 16.16 1 46 0 1
#> 125 15.65 1 67 1 0
#> 18 15.21 1 49 1 0
#> 91 5.33 1 61 0 1
#> 111 17.45 1 47 0 1
#> 127 3.53 1 62 0 1
#> 79 16.23 1 54 1 0
#> 85.1 16.44 1 36 0 0
#> 6 15.64 1 39 0 0
#> 164.1 23.60 1 76 0 1
#> 195 11.76 1 NA 1 0
#> 14 12.89 1 21 0 0
#> 30 17.43 1 78 0 0
#> 77.2 7.27 1 67 0 1
#> 111.1 17.45 1 47 0 1
#> 153.1 21.33 1 55 1 0
#> 155 13.08 1 26 0 0
#> 25.1 6.32 1 34 1 0
#> 133.1 14.65 1 57 0 0
#> 140 12.68 1 59 1 0
#> 195.1 11.76 1 NA 1 0
#> 36.2 21.19 1 48 0 1
#> 89 11.44 1 NA 0 0
#> 32 20.90 1 37 1 0
#> 140.1 12.68 1 59 1 0
#> 133.2 14.65 1 57 0 0
#> 30.1 17.43 1 78 0 0
#> 130 16.47 1 53 0 1
#> 125.1 15.65 1 67 1 0
#> 86.1 23.81 1 58 0 1
#> 169 22.41 1 46 0 0
#> 150 20.33 1 48 0 0
#> 175 21.91 1 43 0 0
#> 179 18.63 1 42 0 0
#> 91.1 5.33 1 61 0 1
#> 188.1 16.16 1 46 0 1
#> 41 18.02 1 40 1 0
#> 130.1 16.47 1 53 0 1
#> 175.1 21.91 1 43 0 0
#> 183.1 9.24 1 67 1 0
#> 107.3 11.18 1 54 1 0
#> 32.1 20.90 1 37 1 0
#> 195.2 11.76 1 NA 1 0
#> 194 22.40 1 38 0 1
#> 113 22.86 1 34 0 0
#> 25.2 6.32 1 34 1 0
#> 114 13.68 1 NA 0 0
#> 93.2 10.33 1 52 0 1
#> 139.1 21.49 1 63 1 0
#> 183.2 9.24 1 67 1 0
#> 8 18.43 1 32 0 0
#> 60 13.15 1 38 1 0
#> 56.1 12.21 1 60 0 0
#> 77.3 7.27 1 67 0 1
#> 10.2 10.53 1 34 0 0
#> 61 10.12 1 36 0 1
#> 134 17.81 1 47 1 0
#> 12 24.00 0 63 0 0
#> 132 24.00 0 55 0 0
#> 173 24.00 0 19 0 1
#> 7 24.00 0 37 1 0
#> 75 24.00 0 21 1 0
#> 121 24.00 0 57 1 0
#> 1 24.00 0 23 1 0
#> 131 24.00 0 66 0 0
#> 21 24.00 0 47 0 0
#> 172 24.00 0 41 0 0
#> 102 24.00 0 49 0 0
#> 3 24.00 0 31 1 0
#> 165 24.00 0 47 0 0
#> 54 24.00 0 53 1 0
#> 120 24.00 0 68 0 1
#> 95 24.00 0 68 0 1
#> 54.1 24.00 0 53 1 0
#> 109 24.00 0 48 0 0
#> 120.1 24.00 0 68 0 1
#> 67 24.00 0 25 0 0
#> 120.2 24.00 0 68 0 1
#> 121.1 24.00 0 57 1 0
#> 33 24.00 0 53 0 0
#> 47 24.00 0 38 0 1
#> 135 24.00 0 58 1 0
#> 53 24.00 0 32 0 1
#> 71 24.00 0 51 0 0
#> 185 24.00 0 44 1 0
#> 172.1 24.00 0 41 0 0
#> 33.1 24.00 0 53 0 0
#> 143 24.00 0 51 0 0
#> 163 24.00 0 66 0 0
#> 161 24.00 0 45 0 0
#> 19 24.00 0 57 0 1
#> 27 24.00 0 63 1 0
#> 28 24.00 0 67 1 0
#> 119 24.00 0 17 0 0
#> 196 24.00 0 19 0 0
#> 120.3 24.00 0 68 0 1
#> 83 24.00 0 6 0 0
#> 115 24.00 0 NA 1 0
#> 17 24.00 0 38 0 1
#> 151 24.00 0 42 0 0
#> 161.1 24.00 0 45 0 0
#> 147 24.00 0 76 1 0
#> 131.1 24.00 0 66 0 0
#> 19.1 24.00 0 57 0 1
#> 17.1 24.00 0 38 0 1
#> 176 24.00 0 43 0 1
#> 161.2 24.00 0 45 0 0
#> 119.1 24.00 0 17 0 0
#> 163.1 24.00 0 66 0 0
#> 27.1 24.00 0 63 1 0
#> 120.4 24.00 0 68 0 1
#> 178 24.00 0 52 1 0
#> 35 24.00 0 51 0 0
#> 83.1 24.00 0 6 0 0
#> 48 24.00 0 31 1 0
#> 151.1 24.00 0 42 0 0
#> 62 24.00 0 71 0 0
#> 19.2 24.00 0 57 0 1
#> 193 24.00 0 45 0 1
#> 72 24.00 0 40 0 1
#> 31 24.00 0 36 0 1
#> 64 24.00 0 43 0 0
#> 74 24.00 0 43 0 1
#> 163.2 24.00 0 66 0 0
#> 148 24.00 0 61 1 0
#> 165.1 24.00 0 47 0 0
#> 31.1 24.00 0 36 0 1
#> 22 24.00 0 52 1 0
#> 165.2 24.00 0 47 0 0
#> 119.2 24.00 0 17 0 0
#> 80 24.00 0 41 0 0
#> 33.2 24.00 0 53 0 0
#> 9 24.00 0 31 1 0
#> 87 24.00 0 27 0 0
#> 152 24.00 0 36 0 1
#> 176.1 24.00 0 43 0 1
#> 120.5 24.00 0 68 0 1
#> 103 24.00 0 56 1 0
#> 22.1 24.00 0 52 1 0
#> 135.1 24.00 0 58 1 0
#> 144 24.00 0 28 0 1
#> 87.1 24.00 0 27 0 0
#> 2 24.00 0 9 0 0
#> 144.1 24.00 0 28 0 1
#> 17.2 24.00 0 38 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.15 NA NA NA
#> 2 age, Cure model 0.0180 NA NA NA
#> 3 grade_ii, Cure model 0.770 NA NA NA
#> 4 grade_iii, Cure model 0.705 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00474 NA NA NA
#> 2 grade_ii, Survival model 0.112 NA NA NA
#> 3 grade_iii, Survival model -0.00411 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.15141 0.01803 0.77045 0.70476
#>
#> Degrees of Freedom: 192 Total (i.e. Null); 189 Residual
#> Null Deviance: 265.7
#> Residual Deviance: 255.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.15141376 0.01803268 0.77044904 0.70475844
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.004737585 0.111644228 -0.004107459
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.16077224 0.57620058 0.61779731 0.36719429 0.28323884 0.33865556
#> [7] 0.22034238 0.48448848 0.02798664 0.78847187 0.12996097 0.73434082
#> [13] 0.09895860 0.93222773 0.69191706 0.78847187 0.00274406 0.36719429
#> [19] 0.88772869 0.69191706 0.75600428 0.51475874 0.01028922 0.42475934
#> [25] 0.64935213 0.84343551 0.12996097 0.75600428 0.62832536 0.43464109
#> [31] 0.22917477 0.02798664 0.67054877 0.26492510 0.83233331 0.04064376
#> [37] 0.47441397 0.88772869 0.54509817 0.05514334 0.11431299 0.62832536
#> [43] 0.01610816 0.20286412 0.73434082 0.22917477 0.19425038 0.67054877
#> [49] 0.48448848 0.05514334 0.69191706 0.12996097 0.87654571 0.21156936
#> [55] 0.40533624 0.44457034 0.50458510 0.96586378 0.30161829 0.98855466
#> [61] 0.39559960 0.36719429 0.46436985 0.01610816 0.58660432 0.31997128
#> [67] 0.88772869 0.30161829 0.11431299 0.56581415 0.93222773 0.51475874
#> [73] 0.59702557 0.12996097 0.16919355 0.59702557 0.51475874 0.31997128
#> [79] 0.34817819 0.44457034 0.00274406 0.06896961 0.18571711 0.08400343
#> [85] 0.24680470 0.96586378 0.40533624 0.27407050 0.34817819 0.08400343
#> [91] 0.84343551 0.69191706 0.16919355 0.07642411 0.04781088 0.93222773
#> [97] 0.78847187 0.09895860 0.84343551 0.25584232 0.55544978 0.64935213
#> [103] 0.88772869 0.75600428 0.82123854 0.29241338 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [193] 0.00000000
#>
#> $Time
#> 90 123 177 85 40 171 58 29 129 93 99 159 139
#> 20.94 13.00 12.53 16.44 18.00 16.57 19.34 15.45 23.41 10.33 21.19 10.55 21.49
#> 25 107 93.1 86 192 77 107.1 10 133 168 100 56 183
#> 6.32 11.18 10.33 23.81 16.44 7.27 11.18 10.53 14.65 23.72 16.07 12.21 9.24
#> 36 10.1 42 26 76 129.1 43 88 101 92 167 77.1 13
#> 21.19 10.53 12.43 15.77 19.22 23.41 12.10 18.37 9.97 22.92 15.55 7.27 14.34
#> 63 153 42.1 164 105 159.1 76.1 158 43.1 29.1 63.1 107.2 36.1
#> 22.77 21.33 12.43 23.60 19.75 10.55 19.22 20.14 12.10 15.45 22.77 11.18 21.19
#> 70 170 188 125 18 91 111 127 79 85.1 6 164.1 14
#> 7.38 19.54 16.16 15.65 15.21 5.33 17.45 3.53 16.23 16.44 15.64 23.60 12.89
#> 30 77.2 111.1 153.1 155 25.1 133.1 140 36.2 32 140.1 133.2 30.1
#> 17.43 7.27 17.45 21.33 13.08 6.32 14.65 12.68 21.19 20.90 12.68 14.65 17.43
#> 130 125.1 86.1 169 150 175 179 91.1 188.1 41 130.1 175.1 183.1
#> 16.47 15.65 23.81 22.41 20.33 21.91 18.63 5.33 16.16 18.02 16.47 21.91 9.24
#> 107.3 32.1 194 113 25.2 93.2 139.1 183.2 8 60 56.1 77.3 10.2
#> 11.18 20.90 22.40 22.86 6.32 10.33 21.49 9.24 18.43 13.15 12.21 7.27 10.53
#> 61 134 12 132 173 7 75 121 1 131 21 172 102
#> 10.12 17.81 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3 165 54 120 95 54.1 109 120.1 67 120.2 121.1 33 47
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135 53 71 185 172.1 33.1 143 163 161 19 27 28 119
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 196 120.3 83 17 151 161.1 147 131.1 19.1 17.1 176 161.2 119.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 163.1 27.1 120.4 178 35 83.1 48 151.1 62 19.2 193 72 31
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64 74 163.2 148 165.1 31.1 22 165.2 119.2 80 33.2 9 87
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152 176.1 120.5 103 22.1 135.1 144 87.1 2 144.1 17.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[10]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.0008783286 0.3934896015 0.2596854108
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.07243310 0.01093159 0.79540066
#> grade_iii, Cure model
#> 1.16699213
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 159 10.55 1 50 0 1
#> 77 7.27 1 67 0 1
#> 117 17.46 1 26 0 1
#> 37 12.52 1 57 1 0
#> 25 6.32 1 34 1 0
#> 136 21.83 1 43 0 1
#> 150 20.33 1 48 0 0
#> 155 13.08 1 26 0 0
#> 97 19.14 1 65 0 1
#> 59 10.16 1 NA 1 0
#> 10 10.53 1 34 0 0
#> 5 16.43 1 51 0 1
#> 29 15.45 1 68 1 0
#> 89 11.44 1 NA 0 0
#> 113 22.86 1 34 0 0
#> 166 19.98 1 48 0 0
#> 114 13.68 1 NA 0 0
#> 16 8.71 1 71 0 1
#> 127 3.53 1 62 0 1
#> 70 7.38 1 30 1 0
#> 57 14.46 1 45 0 1
#> 90 20.94 1 50 0 1
#> 105 19.75 1 60 0 0
#> 4 17.64 1 NA 0 1
#> 194 22.40 1 38 0 1
#> 57.1 14.46 1 45 0 1
#> 189 10.51 1 NA 1 0
#> 140 12.68 1 59 1 0
#> 167 15.55 1 56 1 0
#> 157 15.10 1 47 0 0
#> 145 10.07 1 65 1 0
#> 39 15.59 1 37 0 1
#> 197 21.60 1 69 1 0
#> 36 21.19 1 48 0 1
#> 6 15.64 1 39 0 0
#> 45 17.42 1 54 0 1
#> 45.1 17.42 1 54 0 1
#> 159.1 10.55 1 50 0 1
#> 49 12.19 1 48 1 0
#> 110 17.56 1 65 0 1
#> 99 21.19 1 38 0 1
#> 50 10.02 1 NA 1 0
#> 117.1 17.46 1 26 0 1
#> 24 23.89 1 38 0 0
#> 25.1 6.32 1 34 1 0
#> 77.1 7.27 1 67 0 1
#> 139 21.49 1 63 1 0
#> 136.1 21.83 1 43 0 1
#> 149 8.37 1 33 1 0
#> 145.1 10.07 1 65 1 0
#> 68 20.62 1 44 0 0
#> 171 16.57 1 41 0 1
#> 93 10.33 1 52 0 1
#> 40 18.00 1 28 1 0
#> 183 9.24 1 67 1 0
#> 16.1 8.71 1 71 0 1
#> 199 19.81 1 NA 0 1
#> 23 16.92 1 61 0 0
#> 63 22.77 1 31 1 0
#> 52 10.42 1 52 0 1
#> 134 17.81 1 47 1 0
#> 124 9.73 1 NA 1 0
#> 129 23.41 1 53 1 0
#> 130 16.47 1 53 0 1
#> 199.1 19.81 1 NA 0 1
#> 171.1 16.57 1 41 0 1
#> 60 13.15 1 38 1 0
#> 157.1 15.10 1 47 0 0
#> 91 5.33 1 61 0 1
#> 150.1 20.33 1 48 0 0
#> 167.1 15.55 1 56 1 0
#> 184 17.77 1 38 0 0
#> 106 16.67 1 49 1 0
#> 105.1 19.75 1 60 0 0
#> 43 12.10 1 61 0 1
#> 5.1 16.43 1 51 0 1
#> 107 11.18 1 54 1 0
#> 106.1 16.67 1 49 1 0
#> 91.1 5.33 1 61 0 1
#> 164 23.60 1 76 0 1
#> 56 12.21 1 60 0 0
#> 77.2 7.27 1 67 0 1
#> 164.1 23.60 1 76 0 1
#> 171.2 16.57 1 41 0 1
#> 123 13.00 1 44 1 0
#> 158 20.14 1 74 1 0
#> 45.2 17.42 1 54 0 1
#> 26 15.77 1 49 0 1
#> 106.2 16.67 1 49 1 0
#> 60.1 13.15 1 38 1 0
#> 85 16.44 1 36 0 0
#> 139.1 21.49 1 63 1 0
#> 13 14.34 1 54 0 1
#> 92 22.92 1 47 0 1
#> 194.1 22.40 1 38 0 1
#> 88 18.37 1 47 0 0
#> 76 19.22 1 54 0 1
#> 32 20.90 1 37 1 0
#> 139.2 21.49 1 63 1 0
#> 159.2 10.55 1 50 0 1
#> 76.1 19.22 1 54 0 1
#> 150.2 20.33 1 48 0 0
#> 140.1 12.68 1 59 1 0
#> 32.1 20.90 1 37 1 0
#> 70.1 7.38 1 30 1 0
#> 88.1 18.37 1 47 0 0
#> 39.1 15.59 1 37 0 1
#> 171.3 16.57 1 41 0 1
#> 16.2 8.71 1 71 0 1
#> 99.1 21.19 1 38 0 1
#> 52.1 10.42 1 52 0 1
#> 145.2 10.07 1 65 1 0
#> 1 24.00 0 23 1 0
#> 176 24.00 0 43 0 1
#> 71 24.00 0 51 0 0
#> 64 24.00 0 43 0 0
#> 198 24.00 0 66 0 1
#> 62 24.00 0 71 0 0
#> 152 24.00 0 36 0 1
#> 34 24.00 0 36 0 0
#> 62.1 24.00 0 71 0 0
#> 198.1 24.00 0 66 0 1
#> 112 24.00 0 61 0 0
#> 141 24.00 0 44 1 0
#> 163 24.00 0 66 0 0
#> 172 24.00 0 41 0 0
#> 200 24.00 0 64 0 0
#> 11 24.00 0 42 0 1
#> 84 24.00 0 39 0 1
#> 95 24.00 0 68 0 1
#> 185 24.00 0 44 1 0
#> 102 24.00 0 49 0 0
#> 48 24.00 0 31 1 0
#> 2 24.00 0 9 0 0
#> 147 24.00 0 76 1 0
#> 172.1 24.00 0 41 0 0
#> 119 24.00 0 17 0 0
#> 118 24.00 0 44 1 0
#> 132 24.00 0 55 0 0
#> 132.1 24.00 0 55 0 0
#> 116 24.00 0 58 0 1
#> 174 24.00 0 49 1 0
#> 173 24.00 0 19 0 1
#> 160 24.00 0 31 1 0
#> 74 24.00 0 43 0 1
#> 172.2 24.00 0 41 0 0
#> 2.1 24.00 0 9 0 0
#> 46 24.00 0 71 0 0
#> 174.1 24.00 0 49 1 0
#> 82 24.00 0 34 0 0
#> 198.2 24.00 0 66 0 1
#> 31 24.00 0 36 0 1
#> 132.2 24.00 0 55 0 0
#> 160.1 24.00 0 31 1 0
#> 182 24.00 0 35 0 0
#> 109 24.00 0 48 0 0
#> 165 24.00 0 47 0 0
#> 22 24.00 0 52 1 0
#> 198.3 24.00 0 66 0 1
#> 83 24.00 0 6 0 0
#> 144 24.00 0 28 0 1
#> 143 24.00 0 51 0 0
#> 178 24.00 0 52 1 0
#> 84.1 24.00 0 39 0 1
#> 144.1 24.00 0 28 0 1
#> 11.1 24.00 0 42 0 1
#> 28 24.00 0 67 1 0
#> 71.1 24.00 0 51 0 0
#> 144.2 24.00 0 28 0 1
#> 198.4 24.00 0 66 0 1
#> 131 24.00 0 66 0 0
#> 165.1 24.00 0 47 0 0
#> 46.1 24.00 0 71 0 0
#> 109.1 24.00 0 48 0 0
#> 122 24.00 0 66 0 0
#> 185.1 24.00 0 44 1 0
#> 121 24.00 0 57 1 0
#> 47 24.00 0 38 0 1
#> 67 24.00 0 25 0 0
#> 17 24.00 0 38 0 1
#> 27 24.00 0 63 1 0
#> 17.1 24.00 0 38 0 1
#> 98 24.00 0 34 1 0
#> 163.1 24.00 0 66 0 0
#> 178.1 24.00 0 52 1 0
#> 146 24.00 0 63 1 0
#> 38 24.00 0 31 1 0
#> 62.2 24.00 0 71 0 0
#> 115 24.00 0 NA 1 0
#> 147.1 24.00 0 76 1 0
#> 2.2 24.00 0 9 0 0
#> 146.1 24.00 0 63 1 0
#> 27.1 24.00 0 63 1 0
#> 72 24.00 0 40 0 1
#> 11.2 24.00 0 42 0 1
#> 186 24.00 0 45 1 0
#> 11.3 24.00 0 42 0 1
#> 54 24.00 0 53 1 0
#> 198.5 24.00 0 66 0 1
#> 22.1 24.00 0 52 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.07 NA NA NA
#> 2 age, Cure model 0.0109 NA NA NA
#> 3 grade_ii, Cure model 0.795 NA NA NA
#> 4 grade_iii, Cure model 1.17 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.000878 NA NA NA
#> 2 grade_ii, Survival model 0.393 NA NA NA
#> 3 grade_iii, Survival model 0.260 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.07243 0.01093 0.79540 1.16699
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 262
#> Residual Deviance: 249.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.07243310 0.01093159 0.79540066 1.16699213
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.0008783286 0.3934896015 0.2596854108
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.81582688 0.94282159 0.47938256 0.77665404 0.96435894 0.17638513
#> [7] 0.32174287 0.74478720 0.41175735 0.83867619 0.61203218 0.67953060
#> [13] 0.11769287 0.36202179 0.89893417 0.99288166 0.92828309 0.70425353
#> [19] 0.27998039 0.37217460 0.14919087 0.70425353 0.76087896 0.66295697
#> [25] 0.68781032 0.86917226 0.64614939 0.20221026 0.24825434 0.63761440
#> [31] 0.49797452 0.49797452 0.81582688 0.79241593 0.46987311 0.24825434
#> [37] 0.47938256 0.01891154 0.96435894 0.94282159 0.21507590 0.17638513
#> [43] 0.92092479 0.86917226 0.31133177 0.56057954 0.86156192 0.44100205
#> [49] 0.89147346 0.89893417 0.52506084 0.13392414 0.84636073 0.45070292
#> [55] 0.08413603 0.59469159 0.56057954 0.72873239 0.68781032 0.97865853
#> [61] 0.32174287 0.66295697 0.46029140 0.53424064 0.37217460 0.80025219
#> [67] 0.61203218 0.80806033 0.53424064 0.97865853 0.04974683 0.78453713
#> [73] 0.94282159 0.04974683 0.56057954 0.75285632 0.35185673 0.49797452
#> [79] 0.62907543 0.53424064 0.72873239 0.60336389 0.21507590 0.72056394
#> [85] 0.10139719 0.14919087 0.42159462 0.39214536 0.29083123 0.21507590
#> [91] 0.81582688 0.39214536 0.32174287 0.76087896 0.29083123 0.92828309
#> [97] 0.42159462 0.64614939 0.56057954 0.89893417 0.24825434 0.84636073
#> [103] 0.86917226 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 159 77 117 37 25 136 150 155 97 10 5 29 113
#> 10.55 7.27 17.46 12.52 6.32 21.83 20.33 13.08 19.14 10.53 16.43 15.45 22.86
#> 166 16 127 70 57 90 105 194 57.1 140 167 157 145
#> 19.98 8.71 3.53 7.38 14.46 20.94 19.75 22.40 14.46 12.68 15.55 15.10 10.07
#> 39 197 36 6 45 45.1 159.1 49 110 99 117.1 24 25.1
#> 15.59 21.60 21.19 15.64 17.42 17.42 10.55 12.19 17.56 21.19 17.46 23.89 6.32
#> 77.1 139 136.1 149 145.1 68 171 93 40 183 16.1 23 63
#> 7.27 21.49 21.83 8.37 10.07 20.62 16.57 10.33 18.00 9.24 8.71 16.92 22.77
#> 52 134 129 130 171.1 60 157.1 91 150.1 167.1 184 106 105.1
#> 10.42 17.81 23.41 16.47 16.57 13.15 15.10 5.33 20.33 15.55 17.77 16.67 19.75
#> 43 5.1 107 106.1 91.1 164 56 77.2 164.1 171.2 123 158 45.2
#> 12.10 16.43 11.18 16.67 5.33 23.60 12.21 7.27 23.60 16.57 13.00 20.14 17.42
#> 26 106.2 60.1 85 139.1 13 92 194.1 88 76 32 139.2 159.2
#> 15.77 16.67 13.15 16.44 21.49 14.34 22.92 22.40 18.37 19.22 20.90 21.49 10.55
#> 76.1 150.2 140.1 32.1 70.1 88.1 39.1 171.3 16.2 99.1 52.1 145.2 1
#> 19.22 20.33 12.68 20.90 7.38 18.37 15.59 16.57 8.71 21.19 10.42 10.07 24.00
#> 176 71 64 198 62 152 34 62.1 198.1 112 141 163 172
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 200 11 84 95 185 102 48 2 147 172.1 119 118 132
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 132.1 116 174 173 160 74 172.2 2.1 46 174.1 82 198.2 31
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 132.2 160.1 182 109 165 22 198.3 83 144 143 178 84.1 144.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 11.1 28 71.1 144.2 198.4 131 165.1 46.1 109.1 122 185.1 121 47
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67 17 27 17.1 98 163.1 178.1 146 38 62.2 147.1 2.2 146.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 27.1 72 11.2 186 11.3 54 198.5 22.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[11]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.0007548334 0.8483148256 0.3702501991
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.31446748 -0.00183136 -0.20035112
#> grade_iii, Cure model
#> 0.08264403
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 10 10.53 1 34 0 0
#> 139 21.49 1 63 1 0
#> 40 18.00 1 28 1 0
#> 192 16.44 1 31 1 0
#> 61 10.12 1 36 0 1
#> 166 19.98 1 48 0 0
#> 169 22.41 1 46 0 0
#> 150 20.33 1 48 0 0
#> 66 22.13 1 53 0 0
#> 107 11.18 1 54 1 0
#> 69 23.23 1 25 0 1
#> 85 16.44 1 36 0 0
#> 199 19.81 1 NA 0 1
#> 60 13.15 1 38 1 0
#> 101 9.97 1 10 0 1
#> 52 10.42 1 52 0 1
#> 69.1 23.23 1 25 0 1
#> 50 10.02 1 NA 1 0
#> 127 3.53 1 62 0 1
#> 26 15.77 1 49 0 1
#> 123 13.00 1 44 1 0
#> 59 10.16 1 NA 1 0
#> 52.1 10.42 1 52 0 1
#> 108 18.29 1 39 0 1
#> 150.1 20.33 1 48 0 0
#> 128 20.35 1 35 0 1
#> 130 16.47 1 53 0 1
#> 50.1 10.02 1 NA 1 0
#> 169.1 22.41 1 46 0 0
#> 81 14.06 1 34 0 0
#> 167 15.55 1 56 1 0
#> 175 21.91 1 43 0 0
#> 78 23.88 1 43 0 0
#> 76 19.22 1 54 0 1
#> 79 16.23 1 54 1 0
#> 101.1 9.97 1 10 0 1
#> 6 15.64 1 39 0 0
#> 8 18.43 1 32 0 0
#> 155 13.08 1 26 0 0
#> 6.1 15.64 1 39 0 0
#> 66.1 22.13 1 53 0 0
#> 49 12.19 1 48 1 0
#> 40.1 18.00 1 28 1 0
#> 169.2 22.41 1 46 0 0
#> 88 18.37 1 47 0 0
#> 149 8.37 1 33 1 0
#> 39 15.59 1 37 0 1
#> 97 19.14 1 65 0 1
#> 167.1 15.55 1 56 1 0
#> 180 14.82 1 37 0 0
#> 69.2 23.23 1 25 0 1
#> 37 12.52 1 57 1 0
#> 8.1 18.43 1 32 0 0
#> 195 11.76 1 NA 1 0
#> 25 6.32 1 34 1 0
#> 57 14.46 1 45 0 1
#> 24 23.89 1 38 0 0
#> 128.1 20.35 1 35 0 1
#> 129 23.41 1 53 1 0
#> 125 15.65 1 67 1 0
#> 133 14.65 1 57 0 0
#> 134 17.81 1 47 1 0
#> 190 20.81 1 42 1 0
#> 190.1 20.81 1 42 1 0
#> 192.1 16.44 1 31 1 0
#> 168 23.72 1 70 0 0
#> 59.1 10.16 1 NA 1 0
#> 192.2 16.44 1 31 1 0
#> 51 18.23 1 83 0 1
#> 60.1 13.15 1 38 1 0
#> 159 10.55 1 50 0 1
#> 55 19.34 1 69 0 1
#> 8.2 18.43 1 32 0 0
#> 140 12.68 1 59 1 0
#> 29 15.45 1 68 1 0
#> 128.2 20.35 1 35 0 1
#> 32 20.90 1 37 1 0
#> 153 21.33 1 55 1 0
#> 100 16.07 1 60 0 0
#> 111 17.45 1 47 0 1
#> 61.1 10.12 1 36 0 1
#> 124 9.73 1 NA 1 0
#> 23 16.92 1 61 0 0
#> 123.1 13.00 1 44 1 0
#> 68 20.62 1 44 0 0
#> 89 11.44 1 NA 0 0
#> 51.1 18.23 1 83 0 1
#> 24.1 23.89 1 38 0 0
#> 164 23.60 1 76 0 1
#> 153.1 21.33 1 55 1 0
#> 125.1 15.65 1 67 1 0
#> 170 19.54 1 43 0 1
#> 69.3 23.23 1 25 0 1
#> 91 5.33 1 61 0 1
#> 92 22.92 1 47 0 1
#> 168.1 23.72 1 70 0 0
#> 88.1 18.37 1 47 0 0
#> 40.2 18.00 1 28 1 0
#> 92.1 22.92 1 47 0 1
#> 100.1 16.07 1 60 0 0
#> 96 14.54 1 33 0 1
#> 92.2 22.92 1 47 0 1
#> 106 16.67 1 49 1 0
#> 78.1 23.88 1 43 0 0
#> 101.2 9.97 1 10 0 1
#> 197 21.60 1 69 1 0
#> 113 22.86 1 34 0 0
#> 56 12.21 1 60 0 0
#> 69.4 23.23 1 25 0 1
#> 36 21.19 1 48 0 1
#> 69.5 23.23 1 25 0 1
#> 18 15.21 1 49 1 0
#> 182 24.00 0 35 0 0
#> 131 24.00 0 66 0 0
#> 173 24.00 0 19 0 1
#> 11 24.00 0 42 0 1
#> 132 24.00 0 55 0 0
#> 104 24.00 0 50 1 0
#> 152 24.00 0 36 0 1
#> 65 24.00 0 57 1 0
#> 94 24.00 0 51 0 1
#> 131.1 24.00 0 66 0 0
#> 148 24.00 0 61 1 0
#> 118 24.00 0 44 1 0
#> 109 24.00 0 48 0 0
#> 118.1 24.00 0 44 1 0
#> 71 24.00 0 51 0 0
#> 182.1 24.00 0 35 0 0
#> 3 24.00 0 31 1 0
#> 87 24.00 0 27 0 0
#> 160 24.00 0 31 1 0
#> 185 24.00 0 44 1 0
#> 173.1 24.00 0 19 0 1
#> 156 24.00 0 50 1 0
#> 11.1 24.00 0 42 0 1
#> 80 24.00 0 41 0 0
#> 87.1 24.00 0 27 0 0
#> 163 24.00 0 66 0 0
#> 95 24.00 0 68 0 1
#> 17 24.00 0 38 0 1
#> 198 24.00 0 66 0 1
#> 3.1 24.00 0 31 1 0
#> 185.1 24.00 0 44 1 0
#> 28 24.00 0 67 1 0
#> 3.2 24.00 0 31 1 0
#> 102 24.00 0 49 0 0
#> 98 24.00 0 34 1 0
#> 80.1 24.00 0 41 0 0
#> 94.1 24.00 0 51 0 1
#> 3.3 24.00 0 31 1 0
#> 31 24.00 0 36 0 1
#> 115 24.00 0 NA 1 0
#> 109.1 24.00 0 48 0 0
#> 20 24.00 0 46 1 0
#> 104.1 24.00 0 50 1 0
#> 198.1 24.00 0 66 0 1
#> 64 24.00 0 43 0 0
#> 143 24.00 0 51 0 0
#> 119 24.00 0 17 0 0
#> 84 24.00 0 39 0 1
#> 17.1 24.00 0 38 0 1
#> 131.2 24.00 0 66 0 0
#> 143.1 24.00 0 51 0 0
#> 118.2 24.00 0 44 1 0
#> 120 24.00 0 68 0 1
#> 47 24.00 0 38 0 1
#> 104.2 24.00 0 50 1 0
#> 3.4 24.00 0 31 1 0
#> 144 24.00 0 28 0 1
#> 48 24.00 0 31 1 0
#> 120.1 24.00 0 68 0 1
#> 200 24.00 0 64 0 0
#> 65.1 24.00 0 57 1 0
#> 74 24.00 0 43 0 1
#> 67 24.00 0 25 0 0
#> 53 24.00 0 32 0 1
#> 121 24.00 0 57 1 0
#> 73 24.00 0 NA 0 1
#> 3.5 24.00 0 31 1 0
#> 198.2 24.00 0 66 0 1
#> 47.1 24.00 0 38 0 1
#> 72 24.00 0 40 0 1
#> 3.6 24.00 0 31 1 0
#> 103 24.00 0 56 1 0
#> 82 24.00 0 34 0 0
#> 112 24.00 0 61 0 0
#> 126 24.00 0 48 0 0
#> 141 24.00 0 44 1 0
#> 7 24.00 0 37 1 0
#> 146 24.00 0 63 1 0
#> 72.1 24.00 0 40 0 1
#> 186 24.00 0 45 1 0
#> 1 24.00 0 23 1 0
#> 120.2 24.00 0 68 0 1
#> 196 24.00 0 19 0 0
#> 120.3 24.00 0 68 0 1
#> 121.1 24.00 0 57 1 0
#> 19 24.00 0 57 0 1
#> 131.3 24.00 0 66 0 0
#> 143.2 24.00 0 51 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.314 NA NA NA
#> 2 age, Cure model -0.00183 NA NA NA
#> 3 grade_ii, Cure model -0.200 NA NA NA
#> 4 grade_iii, Cure model 0.0826 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.000755 NA NA NA
#> 2 grade_ii, Survival model 0.848 NA NA NA
#> 3 grade_iii, Survival model 0.370 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.314467 -0.001831 -0.200351 0.082644
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 261.7
#> Residual Deviance: 261 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.31446748 -0.00183136 -0.20035112 0.08264403
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.0007548334 0.8483148256 0.3702501991
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.92338247 0.37422417 0.62005950 0.68652916 0.94285987 0.50193571
#> [7] 0.29029254 0.48338739 0.32582655 0.91030350 0.17363123 0.68652916
#> [13] 0.84936733 0.95573346 0.92991393 0.17363123 0.99373469 0.74019194
#> [19] 0.87009797 0.92991393 0.59317455 0.48338739 0.45587086 0.67837767
#> [25] 0.29029254 0.84229191 0.78506941 0.35003993 0.05732266 0.52984004
#> [31] 0.71719380 0.95573346 0.76273317 0.54813127 0.86316850 0.76273317
#> [37] 0.32582655 0.90369576 0.62005950 0.29029254 0.57505943 0.97481075
#> [43] 0.77761952 0.53901504 0.78506941 0.81387644 0.17363123 0.89036032
#> [49] 0.54813127 0.98115850 0.83521801 0.02048303 0.45587086 0.15608738
#> [55] 0.74785526 0.82099695 0.64520344 0.42727328 0.42727328 0.68652916
#> [61] 0.09598735 0.68652916 0.60224567 0.84936733 0.91685219 0.52060262
#> [67] 0.54813127 0.88363135 0.79955938 0.45587086 0.41709159 0.38562789
#> [73] 0.72488226 0.65355812 0.94285987 0.66187055 0.87009797 0.44626501
#> [79] 0.60224567 0.02048303 0.13569889 0.38562789 0.74785526 0.51130340
#> [85] 0.17363123 0.98745427 0.24270876 0.09598735 0.57505943 0.62005950
#> [91] 0.24270876 0.72488226 0.82812007 0.24270876 0.67018768 0.05732266
#> [97] 0.95573346 0.36237747 0.27798440 0.89702694 0.17363123 0.40658381
#> [103] 0.17363123 0.80675764 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 10 139 40 192 61 166 169 150 66 107 69 85 60
#> 10.53 21.49 18.00 16.44 10.12 19.98 22.41 20.33 22.13 11.18 23.23 16.44 13.15
#> 101 52 69.1 127 26 123 52.1 108 150.1 128 130 169.1 81
#> 9.97 10.42 23.23 3.53 15.77 13.00 10.42 18.29 20.33 20.35 16.47 22.41 14.06
#> 167 175 78 76 79 101.1 6 8 155 6.1 66.1 49 40.1
#> 15.55 21.91 23.88 19.22 16.23 9.97 15.64 18.43 13.08 15.64 22.13 12.19 18.00
#> 169.2 88 149 39 97 167.1 180 69.2 37 8.1 25 57 24
#> 22.41 18.37 8.37 15.59 19.14 15.55 14.82 23.23 12.52 18.43 6.32 14.46 23.89
#> 128.1 129 125 133 134 190 190.1 192.1 168 192.2 51 60.1 159
#> 20.35 23.41 15.65 14.65 17.81 20.81 20.81 16.44 23.72 16.44 18.23 13.15 10.55
#> 55 8.2 140 29 128.2 32 153 100 111 61.1 23 123.1 68
#> 19.34 18.43 12.68 15.45 20.35 20.90 21.33 16.07 17.45 10.12 16.92 13.00 20.62
#> 51.1 24.1 164 153.1 125.1 170 69.3 91 92 168.1 88.1 40.2 92.1
#> 18.23 23.89 23.60 21.33 15.65 19.54 23.23 5.33 22.92 23.72 18.37 18.00 22.92
#> 100.1 96 92.2 106 78.1 101.2 197 113 56 69.4 36 69.5 18
#> 16.07 14.54 22.92 16.67 23.88 9.97 21.60 22.86 12.21 23.23 21.19 23.23 15.21
#> 182 131 173 11 132 104 152 65 94 131.1 148 118 109
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 118.1 71 182.1 3 87 160 185 173.1 156 11.1 80 87.1 163
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95 17 198 3.1 185.1 28 3.2 102 98 80.1 94.1 3.3 31
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 109.1 20 104.1 198.1 64 143 119 84 17.1 131.2 143.1 118.2 120
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 47 104.2 3.4 144 48 120.1 200 65.1 74 67 53 121 3.5
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 198.2 47.1 72 3.6 103 82 112 126 141 7 146 72.1 186
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1 120.2 196 120.3 121.1 19 131.3 143.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[12]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.002545827 0.430319949 0.325224016
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.396867285 0.007538921 0.059403696
#> grade_iii, Cure model
#> 0.733190226
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 15 22.68 1 48 0 0
#> 58 19.34 1 39 0 0
#> 117 17.46 1 26 0 1
#> 41 18.02 1 40 1 0
#> 175 21.91 1 43 0 0
#> 133 14.65 1 57 0 0
#> 93 10.33 1 52 0 1
#> 190 20.81 1 42 1 0
#> 93.1 10.33 1 52 0 1
#> 92 22.92 1 47 0 1
#> 85 16.44 1 36 0 0
#> 189 10.51 1 NA 1 0
#> 177 12.53 1 75 0 0
#> 159 10.55 1 50 0 1
#> 23 16.92 1 61 0 0
#> 18 15.21 1 49 1 0
#> 183 9.24 1 67 1 0
#> 136 21.83 1 43 0 1
#> 123 13.00 1 44 1 0
#> 23.1 16.92 1 61 0 0
#> 97 19.14 1 65 0 1
#> 18.1 15.21 1 49 1 0
#> 10 10.53 1 34 0 0
#> 134 17.81 1 47 1 0
#> 130 16.47 1 53 0 1
#> 26 15.77 1 49 0 1
#> 29 15.45 1 68 1 0
#> 106 16.67 1 49 1 0
#> 184 17.77 1 38 0 0
#> 69 23.23 1 25 0 1
#> 89 11.44 1 NA 0 0
#> 78 23.88 1 43 0 0
#> 85.1 16.44 1 36 0 0
#> 184.1 17.77 1 38 0 0
#> 184.2 17.77 1 38 0 0
#> 180 14.82 1 37 0 0
#> 50 10.02 1 NA 1 0
#> 51 18.23 1 83 0 1
#> 61 10.12 1 36 0 1
#> 70 7.38 1 30 1 0
#> 93.2 10.33 1 52 0 1
#> 93.3 10.33 1 52 0 1
#> 134.1 17.81 1 47 1 0
#> 30 17.43 1 78 0 0
#> 6 15.64 1 39 0 0
#> 154 12.63 1 20 1 0
#> 192 16.44 1 31 1 0
#> 101 9.97 1 10 0 1
#> 194 22.40 1 38 0 1
#> 79 16.23 1 54 1 0
#> 168 23.72 1 70 0 0
#> 153 21.33 1 55 1 0
#> 30.1 17.43 1 78 0 0
#> 76 19.22 1 54 0 1
#> 110 17.56 1 65 0 1
#> 10.1 10.53 1 34 0 0
#> 5 16.43 1 51 0 1
#> 149 8.37 1 33 1 0
#> 55 19.34 1 69 0 1
#> 139 21.49 1 63 1 0
#> 153.1 21.33 1 55 1 0
#> 58.1 19.34 1 39 0 0
#> 153.2 21.33 1 55 1 0
#> 63 22.77 1 31 1 0
#> 106.1 16.67 1 49 1 0
#> 136.1 21.83 1 43 0 1
#> 92.1 22.92 1 47 0 1
#> 168.1 23.72 1 70 0 0
#> 57 14.46 1 45 0 1
#> 86 23.81 1 58 0 1
#> 18.2 15.21 1 49 1 0
#> 52 10.42 1 52 0 1
#> 50.1 10.02 1 NA 1 0
#> 51.1 18.23 1 83 0 1
#> 190.1 20.81 1 42 1 0
#> 30.2 17.43 1 78 0 0
#> 107 11.18 1 54 1 0
#> 16 8.71 1 71 0 1
#> 77 7.27 1 67 0 1
#> 63.1 22.77 1 31 1 0
#> 158 20.14 1 74 1 0
#> 55.1 19.34 1 69 0 1
#> 199 19.81 1 NA 0 1
#> 85.2 16.44 1 36 0 0
#> 166 19.98 1 48 0 0
#> 36 21.19 1 48 0 1
#> 111 17.45 1 47 0 1
#> 111.1 17.45 1 47 0 1
#> 76.1 19.22 1 54 0 1
#> 88 18.37 1 47 0 0
#> 134.2 17.81 1 47 1 0
#> 90 20.94 1 50 0 1
#> 63.2 22.77 1 31 1 0
#> 100 16.07 1 60 0 0
#> 39 15.59 1 37 0 1
#> 153.3 21.33 1 55 1 0
#> 26.1 15.77 1 49 0 1
#> 25 6.32 1 34 1 0
#> 66 22.13 1 53 0 0
#> 169 22.41 1 46 0 0
#> 14 12.89 1 21 0 0
#> 97.1 19.14 1 65 0 1
#> 177.1 12.53 1 75 0 0
#> 168.2 23.72 1 70 0 0
#> 145 10.07 1 65 1 0
#> 24 23.89 1 38 0 0
#> 91 5.33 1 61 0 1
#> 10.2 10.53 1 34 0 0
#> 93.4 10.33 1 52 0 1
#> 125 15.65 1 67 1 0
#> 183.1 9.24 1 67 1 0
#> 29.1 15.45 1 68 1 0
#> 137 24.00 0 45 1 0
#> 148 24.00 0 61 1 0
#> 3 24.00 0 31 1 0
#> 48 24.00 0 31 1 0
#> 102 24.00 0 49 0 0
#> 138 24.00 0 44 1 0
#> 191 24.00 0 60 0 1
#> 186 24.00 0 45 1 0
#> 131 24.00 0 66 0 0
#> 38 24.00 0 31 1 0
#> 172 24.00 0 41 0 0
#> 9 24.00 0 31 1 0
#> 109 24.00 0 48 0 0
#> 178 24.00 0 52 1 0
#> 11 24.00 0 42 0 1
#> 95 24.00 0 68 0 1
#> 2 24.00 0 9 0 0
#> 116 24.00 0 58 0 1
#> 11.1 24.00 0 42 0 1
#> 161 24.00 0 45 0 0
#> 191.1 24.00 0 60 0 1
#> 33 24.00 0 53 0 0
#> 162 24.00 0 51 0 0
#> 165 24.00 0 47 0 0
#> 121 24.00 0 57 1 0
#> 72 24.00 0 40 0 1
#> 112 24.00 0 61 0 0
#> 72.1 24.00 0 40 0 1
#> 120 24.00 0 68 0 1
#> 116.1 24.00 0 58 0 1
#> 186.1 24.00 0 45 1 0
#> 73 24.00 0 NA 0 1
#> 142 24.00 0 53 0 0
#> 75 24.00 0 21 1 0
#> 151 24.00 0 42 0 0
#> 193 24.00 0 45 0 1
#> 200 24.00 0 64 0 0
#> 34 24.00 0 36 0 0
#> 53 24.00 0 32 0 1
#> 54 24.00 0 53 1 0
#> 161.1 24.00 0 45 0 0
#> 48.1 24.00 0 31 1 0
#> 163 24.00 0 66 0 0
#> 142.1 24.00 0 53 0 0
#> 103 24.00 0 56 1 0
#> 20 24.00 0 46 1 0
#> 95.1 24.00 0 68 0 1
#> 119 24.00 0 17 0 0
#> 191.2 24.00 0 60 0 1
#> 135 24.00 0 58 1 0
#> 162.1 24.00 0 51 0 0
#> 80 24.00 0 41 0 0
#> 28 24.00 0 67 1 0
#> 38.1 24.00 0 31 1 0
#> 146 24.00 0 63 1 0
#> 65 24.00 0 57 1 0
#> 147 24.00 0 76 1 0
#> 2.1 24.00 0 9 0 0
#> 198 24.00 0 66 0 1
#> 186.2 24.00 0 45 1 0
#> 121.1 24.00 0 57 1 0
#> 12 24.00 0 63 0 0
#> 38.2 24.00 0 31 1 0
#> 152 24.00 0 36 0 1
#> 200.1 24.00 0 64 0 0
#> 172.1 24.00 0 41 0 0
#> 173 24.00 0 19 0 1
#> 132 24.00 0 55 0 0
#> 28.1 24.00 0 67 1 0
#> 118 24.00 0 44 1 0
#> 33.1 24.00 0 53 0 0
#> 104 24.00 0 50 1 0
#> 54.1 24.00 0 53 1 0
#> 35 24.00 0 51 0 0
#> 121.2 24.00 0 57 1 0
#> 172.2 24.00 0 41 0 0
#> 71 24.00 0 51 0 0
#> 182 24.00 0 35 0 0
#> 28.2 24.00 0 67 1 0
#> 104.1 24.00 0 50 1 0
#> 122 24.00 0 66 0 0
#> 104.2 24.00 0 50 1 0
#> 17 24.00 0 38 0 1
#> 74 24.00 0 43 0 1
#> 80.1 24.00 0 41 0 0
#> 64 24.00 0 43 0 0
#> 131.1 24.00 0 66 0 0
#> 162.2 24.00 0 51 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.397 NA NA NA
#> 2 age, Cure model 0.00754 NA NA NA
#> 3 grade_ii, Cure model 0.0594 NA NA NA
#> 4 grade_iii, Cure model 0.733 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00255 NA NA NA
#> 2 grade_ii, Survival model 0.430 NA NA NA
#> 3 grade_iii, Survival model 0.325 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.396867 0.007539 0.059404 0.733190
#>
#> Degrees of Freedom: 193 Total (i.e. Null); 190 Residual
#> Null Deviance: 266.9
#> Residual Deviance: 261.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.396867285 0.007538921 0.059403696 0.733190226
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.002545827 0.430319949 0.325224016
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.23249393 0.43136674 0.59338739 0.52844693 0.28421922 0.80905724
#> [7] 0.89746132 0.39282389 0.89746132 0.16496241 0.67879465 0.84356295
#> [13] 0.86394063 0.64038710 0.78134124 0.94933522 0.29682987 0.82294564
#> [19] 0.64038710 0.48513799 0.78134124 0.87069344 0.53693553 0.67117238
#> [25] 0.73080227 0.76716808 0.65591374 0.56117167 0.14739787 0.04820488
#> [31] 0.67879465 0.56117167 0.56117167 0.80208736 0.51141542 0.92981275
#> [37] 0.97484929 0.89746132 0.89746132 0.53693553 0.61714482 0.75267047
#> [43] 0.83671477 0.67879465 0.94285257 0.25878206 0.71595284 0.09830929
#> [49] 0.33212932 0.61714482 0.46725004 0.58530213 0.87069344 0.70846241
#> [55] 0.96849522 0.43136674 0.32044764 0.33212932 0.43136674 0.33212932
#> [61] 0.19487192 0.65591374 0.29682987 0.16496241 0.09830929 0.81601776
#> [67] 0.07567643 0.78134124 0.89075331 0.51141542 0.39282389 0.61714482
#> [73] 0.85715748 0.96211298 0.98117616 0.19487192 0.41218853 0.43136674
#> [79] 0.67879465 0.42179179 0.37233599 0.60142021 0.60142021 0.46725004
#> [85] 0.50261779 0.53693553 0.38265839 0.19487192 0.72338385 0.75993729
#> [91] 0.33212932 0.73080227 0.98747694 0.27154361 0.24568159 0.82983177
#> [97] 0.48513799 0.84356295 0.09830929 0.93635115 0.01944655 0.99375064
#> [103] 0.87069344 0.89746132 0.74539632 0.94933522 0.76716808 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [193] 0.00000000 0.00000000
#>
#> $Time
#> 15 58 117 41 175 133 93 190 93.1 92 85 177 159
#> 22.68 19.34 17.46 18.02 21.91 14.65 10.33 20.81 10.33 22.92 16.44 12.53 10.55
#> 23 18 183 136 123 23.1 97 18.1 10 134 130 26 29
#> 16.92 15.21 9.24 21.83 13.00 16.92 19.14 15.21 10.53 17.81 16.47 15.77 15.45
#> 106 184 69 78 85.1 184.1 184.2 180 51 61 70 93.2 93.3
#> 16.67 17.77 23.23 23.88 16.44 17.77 17.77 14.82 18.23 10.12 7.38 10.33 10.33
#> 134.1 30 6 154 192 101 194 79 168 153 30.1 76 110
#> 17.81 17.43 15.64 12.63 16.44 9.97 22.40 16.23 23.72 21.33 17.43 19.22 17.56
#> 10.1 5 149 55 139 153.1 58.1 153.2 63 106.1 136.1 92.1 168.1
#> 10.53 16.43 8.37 19.34 21.49 21.33 19.34 21.33 22.77 16.67 21.83 22.92 23.72
#> 57 86 18.2 52 51.1 190.1 30.2 107 16 77 63.1 158 55.1
#> 14.46 23.81 15.21 10.42 18.23 20.81 17.43 11.18 8.71 7.27 22.77 20.14 19.34
#> 85.2 166 36 111 111.1 76.1 88 134.2 90 63.2 100 39 153.3
#> 16.44 19.98 21.19 17.45 17.45 19.22 18.37 17.81 20.94 22.77 16.07 15.59 21.33
#> 26.1 25 66 169 14 97.1 177.1 168.2 145 24 91 10.2 93.4
#> 15.77 6.32 22.13 22.41 12.89 19.14 12.53 23.72 10.07 23.89 5.33 10.53 10.33
#> 125 183.1 29.1 137 148 3 48 102 138 191 186 131 38
#> 15.65 9.24 15.45 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172 9 109 178 11 95 2 116 11.1 161 191.1 33 162
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165 121 72 112 72.1 120 116.1 186.1 142 75 151 193 200
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34 53 54 161.1 48.1 163 142.1 103 20 95.1 119 191.2 135
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 162.1 80 28 38.1 146 65 147 2.1 198 186.2 121.1 12 38.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152 200.1 172.1 173 132 28.1 118 33.1 104 54.1 35 121.2 172.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71 182 28.2 104.1 122 104.2 17 74 80.1 64 131.1 162.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[13]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.00493963 0.62964522 0.37123774
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.338967871 0.005032584 0.220652605
#> grade_iii, Cure model
#> 0.785079788
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 197 21.60 1 69 1 0
#> 23 16.92 1 61 0 0
#> 140 12.68 1 59 1 0
#> 110 17.56 1 65 0 1
#> 52 10.42 1 52 0 1
#> 58 19.34 1 39 0 0
#> 4 17.64 1 NA 0 1
#> 149 8.37 1 33 1 0
#> 140.1 12.68 1 59 1 0
#> 36 21.19 1 48 0 1
#> 127 3.53 1 62 0 1
#> 6 15.64 1 39 0 0
#> 58.1 19.34 1 39 0 0
#> 68 20.62 1 44 0 0
#> 124 9.73 1 NA 1 0
#> 26 15.77 1 49 0 1
#> 85 16.44 1 36 0 0
#> 56 12.21 1 60 0 0
#> 149.1 8.37 1 33 1 0
#> 180 14.82 1 37 0 0
#> 30 17.43 1 78 0 0
#> 157 15.10 1 47 0 0
#> 76 19.22 1 54 0 1
#> 159 10.55 1 50 0 1
#> 66 22.13 1 53 0 0
#> 41 18.02 1 40 1 0
#> 18 15.21 1 49 1 0
#> 199 19.81 1 NA 0 1
#> 166 19.98 1 48 0 0
#> 181 16.46 1 45 0 1
#> 41.1 18.02 1 40 1 0
#> 106 16.67 1 49 1 0
#> 157.1 15.10 1 47 0 0
#> 111 17.45 1 47 0 1
#> 153 21.33 1 55 1 0
#> 133 14.65 1 57 0 0
#> 183 9.24 1 67 1 0
#> 90 20.94 1 50 0 1
#> 159.1 10.55 1 50 0 1
#> 81 14.06 1 34 0 0
#> 175 21.91 1 43 0 0
#> 199.1 19.81 1 NA 0 1
#> 194 22.40 1 38 0 1
#> 150 20.33 1 48 0 0
#> 45 17.42 1 54 0 1
#> 157.2 15.10 1 47 0 0
#> 164 23.60 1 76 0 1
#> 77 7.27 1 67 0 1
#> 10 10.53 1 34 0 0
#> 90.1 20.94 1 50 0 1
#> 24 23.89 1 38 0 0
#> 168 23.72 1 70 0 0
#> 5 16.43 1 51 0 1
#> 108 18.29 1 39 0 1
#> 51 18.23 1 83 0 1
#> 149.2 8.37 1 33 1 0
#> 63 22.77 1 31 1 0
#> 60 13.15 1 38 1 0
#> 105 19.75 1 60 0 0
#> 199.2 19.81 1 NA 0 1
#> 149.3 8.37 1 33 1 0
#> 14 12.89 1 21 0 0
#> 107 11.18 1 54 1 0
#> 113 22.86 1 34 0 0
#> 168.1 23.72 1 70 0 0
#> 192 16.44 1 31 1 0
#> 26.1 15.77 1 49 0 1
#> 177 12.53 1 75 0 0
#> 188 16.16 1 46 0 1
#> 69 23.23 1 25 0 1
#> 184 17.77 1 38 0 0
#> 106.1 16.67 1 49 1 0
#> 29 15.45 1 68 1 0
#> 85.1 16.44 1 36 0 0
#> 195 11.76 1 NA 1 0
#> 66.1 22.13 1 53 0 0
#> 40 18.00 1 28 1 0
#> 91 5.33 1 61 0 1
#> 139 21.49 1 63 1 0
#> 40.1 18.00 1 28 1 0
#> 70 7.38 1 30 1 0
#> 189 10.51 1 NA 1 0
#> 180.1 14.82 1 37 0 0
#> 61 10.12 1 36 0 1
#> 184.1 17.77 1 38 0 0
#> 110.1 17.56 1 65 0 1
#> 93 10.33 1 52 0 1
#> 171 16.57 1 41 0 1
#> 15 22.68 1 48 0 0
#> 167 15.55 1 56 1 0
#> 101 9.97 1 10 0 1
#> 97 19.14 1 65 0 1
#> 43 12.10 1 61 0 1
#> 43.1 12.10 1 61 0 1
#> 60.1 13.15 1 38 1 0
#> 45.1 17.42 1 54 0 1
#> 56.1 12.21 1 60 0 0
#> 6.1 15.64 1 39 0 0
#> 192.1 16.44 1 31 1 0
#> 180.2 14.82 1 37 0 0
#> 130 16.47 1 53 0 1
#> 32 20.90 1 37 1 0
#> 10.1 10.53 1 34 0 0
#> 154 12.63 1 20 1 0
#> 78 23.88 1 43 0 0
#> 92 22.92 1 47 0 1
#> 58.2 19.34 1 39 0 0
#> 111.1 17.45 1 47 0 1
#> 59 10.16 1 NA 1 0
#> 37 12.52 1 57 1 0
#> 76.1 19.22 1 54 0 1
#> 140.2 12.68 1 59 1 0
#> 12 24.00 0 63 0 0
#> 7 24.00 0 37 1 0
#> 33 24.00 0 53 0 0
#> 3 24.00 0 31 1 0
#> 33.1 24.00 0 53 0 0
#> 83 24.00 0 6 0 0
#> 48 24.00 0 31 1 0
#> 178 24.00 0 52 1 0
#> 118 24.00 0 44 1 0
#> 12.1 24.00 0 63 0 0
#> 73 24.00 0 NA 0 1
#> 38 24.00 0 31 1 0
#> 87 24.00 0 27 0 0
#> 121 24.00 0 57 1 0
#> 53 24.00 0 32 0 1
#> 38.1 24.00 0 31 1 0
#> 87.1 24.00 0 27 0 0
#> 172 24.00 0 41 0 0
#> 148 24.00 0 61 1 0
#> 152 24.00 0 36 0 1
#> 82 24.00 0 34 0 0
#> 161 24.00 0 45 0 0
#> 9 24.00 0 31 1 0
#> 142 24.00 0 53 0 0
#> 118.1 24.00 0 44 1 0
#> 112 24.00 0 61 0 0
#> 126 24.00 0 48 0 0
#> 38.2 24.00 0 31 1 0
#> 3.1 24.00 0 31 1 0
#> 46 24.00 0 71 0 0
#> 162 24.00 0 51 0 0
#> 9.1 24.00 0 31 1 0
#> 161.1 24.00 0 45 0 0
#> 172.1 24.00 0 41 0 0
#> 141 24.00 0 44 1 0
#> 31 24.00 0 36 0 1
#> 71 24.00 0 51 0 0
#> 22 24.00 0 52 1 0
#> 161.2 24.00 0 45 0 0
#> 80 24.00 0 41 0 0
#> 193 24.00 0 45 0 1
#> 62 24.00 0 71 0 0
#> 84 24.00 0 39 0 1
#> 146 24.00 0 63 1 0
#> 1 24.00 0 23 1 0
#> 120 24.00 0 68 0 1
#> 54 24.00 0 53 1 0
#> 196 24.00 0 19 0 0
#> 11 24.00 0 42 0 1
#> 148.1 24.00 0 61 1 0
#> 31.1 24.00 0 36 0 1
#> 147 24.00 0 76 1 0
#> 148.2 24.00 0 61 1 0
#> 71.1 24.00 0 51 0 0
#> 126.1 24.00 0 48 0 0
#> 54.1 24.00 0 53 1 0
#> 163 24.00 0 66 0 0
#> 83.1 24.00 0 6 0 0
#> 163.1 24.00 0 66 0 0
#> 109 24.00 0 48 0 0
#> 163.2 24.00 0 66 0 0
#> 116 24.00 0 58 0 1
#> 72 24.00 0 40 0 1
#> 196.1 24.00 0 19 0 0
#> 46.1 24.00 0 71 0 0
#> 176 24.00 0 43 0 1
#> 35 24.00 0 51 0 0
#> 112.1 24.00 0 61 0 0
#> 12.2 24.00 0 63 0 0
#> 28 24.00 0 67 1 0
#> 161.3 24.00 0 45 0 0
#> 116.1 24.00 0 58 0 1
#> 102 24.00 0 49 0 0
#> 95 24.00 0 68 0 1
#> 31.2 24.00 0 36 0 1
#> 185 24.00 0 44 1 0
#> 200 24.00 0 64 0 0
#> 47 24.00 0 38 0 1
#> 74 24.00 0 43 0 1
#> 44 24.00 0 56 0 0
#> 67 24.00 0 25 0 0
#> 72.1 24.00 0 40 0 1
#> 109.1 24.00 0 48 0 0
#> 75 24.00 0 21 1 0
#> 163.3 24.00 0 66 0 0
#> 176.1 24.00 0 43 0 1
#> 44.1 24.00 0 56 0 0
#> 7.1 24.00 0 37 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.339 NA NA NA
#> 2 age, Cure model 0.00503 NA NA NA
#> 3 grade_ii, Cure model 0.221 NA NA NA
#> 4 grade_iii, Cure model 0.785 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00494 NA NA NA
#> 2 grade_ii, Survival model 0.630 NA NA NA
#> 3 grade_iii, Survival model 0.371 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.338968 0.005033 0.220653 0.785080
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 263.3
#> Residual Deviance: 258.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.338967871 0.005032584 0.220652605 0.785079788
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.00493963 0.62964522 0.37123774
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.155659402 0.476662282 0.753266658 0.409386954 0.887131685 0.269113799
#> [7] 0.931578495 0.753266658 0.187939278 0.991423849 0.606971368 0.269113799
#> [13] 0.228316691 0.588669381 0.533799480 0.806921031 0.931578495 0.680014358
#> [19] 0.447759872 0.652849937 0.299565564 0.851611449 0.122962046 0.351173361
#> [25] 0.643746206 0.248529144 0.524330303 0.351173361 0.486396923 0.652849937
#> [31] 0.428637402 0.177450565 0.707361377 0.922742078 0.198344801 0.851611449
#> [37] 0.716626800 0.144362941 0.112206907 0.238377671 0.457492612 0.652849937
#> [43] 0.043820022 0.974256152 0.869343515 0.198344801 0.003698015 0.022759061
#> [49] 0.570119875 0.330477583 0.340819489 0.931578495 0.090521099 0.725910783
#> [55] 0.258768952 0.931578495 0.744103103 0.842674034 0.078968843 0.022759061
#> [61] 0.533799480 0.588669381 0.788990608 0.579406125 0.056097160 0.390090006
#> [67] 0.486396923 0.634581114 0.533799480 0.122962046 0.370955212 0.982842715
#> [73] 0.166688322 0.370955212 0.965666478 0.680014358 0.904977362 0.390090006
#> [79] 0.409386954 0.896059906 0.505316567 0.101241014 0.625370604 0.913876108
#> [85] 0.320072037 0.824811554 0.824811554 0.725910783 0.457492612 0.806921031
#> [91] 0.606971368 0.533799480 0.680014358 0.514833583 0.218341635 0.869343515
#> [97] 0.780036005 0.012357646 0.067674476 0.269113799 0.428637402 0.797976787
#> [103] 0.299565564 0.753266658 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 197 23 140 110 52 58 149 140.1 36 127 6 58.1 68
#> 21.60 16.92 12.68 17.56 10.42 19.34 8.37 12.68 21.19 3.53 15.64 19.34 20.62
#> 26 85 56 149.1 180 30 157 76 159 66 41 18 166
#> 15.77 16.44 12.21 8.37 14.82 17.43 15.10 19.22 10.55 22.13 18.02 15.21 19.98
#> 181 41.1 106 157.1 111 153 133 183 90 159.1 81 175 194
#> 16.46 18.02 16.67 15.10 17.45 21.33 14.65 9.24 20.94 10.55 14.06 21.91 22.40
#> 150 45 157.2 164 77 10 90.1 24 168 5 108 51 149.2
#> 20.33 17.42 15.10 23.60 7.27 10.53 20.94 23.89 23.72 16.43 18.29 18.23 8.37
#> 63 60 105 149.3 14 107 113 168.1 192 26.1 177 188 69
#> 22.77 13.15 19.75 8.37 12.89 11.18 22.86 23.72 16.44 15.77 12.53 16.16 23.23
#> 184 106.1 29 85.1 66.1 40 91 139 40.1 70 180.1 61 184.1
#> 17.77 16.67 15.45 16.44 22.13 18.00 5.33 21.49 18.00 7.38 14.82 10.12 17.77
#> 110.1 93 171 15 167 101 97 43 43.1 60.1 45.1 56.1 6.1
#> 17.56 10.33 16.57 22.68 15.55 9.97 19.14 12.10 12.10 13.15 17.42 12.21 15.64
#> 192.1 180.2 130 32 10.1 154 78 92 58.2 111.1 37 76.1 140.2
#> 16.44 14.82 16.47 20.90 10.53 12.63 23.88 22.92 19.34 17.45 12.52 19.22 12.68
#> 12 7 33 3 33.1 83 48 178 118 12.1 38 87 121
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53 38.1 87.1 172 148 152 82 161 9 142 118.1 112 126
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 38.2 3.1 46 162 9.1 161.1 172.1 141 31 71 22 161.2 80
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193 62 84 146 1 120 54 196 11 148.1 31.1 147 148.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71.1 126.1 54.1 163 83.1 163.1 109 163.2 116 72 196.1 46.1 176
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 35 112.1 12.2 28 161.3 116.1 102 95 31.2 185 200 47 74
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44 67 72.1 109.1 75 163.3 176.1 44.1 7.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[14]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01696934 0.50960992 -0.01054740
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.246235831 0.009295983 -0.490021337
#> grade_iii, Cure model
#> 0.400469757
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 111 17.45 1 47 0 1
#> 153 21.33 1 55 1 0
#> 81 14.06 1 34 0 0
#> 107 11.18 1 54 1 0
#> 49 12.19 1 48 1 0
#> 107.1 11.18 1 54 1 0
#> 117 17.46 1 26 0 1
#> 77 7.27 1 67 0 1
#> 110 17.56 1 65 0 1
#> 41 18.02 1 40 1 0
#> 50 10.02 1 NA 1 0
#> 57 14.46 1 45 0 1
#> 181 16.46 1 45 0 1
#> 43 12.10 1 61 0 1
#> 149 8.37 1 33 1 0
#> 183 9.24 1 67 1 0
#> 39 15.59 1 37 0 1
#> 56 12.21 1 60 0 0
#> 188 16.16 1 46 0 1
#> 164 23.60 1 76 0 1
#> 117.1 17.46 1 26 0 1
#> 183.1 9.24 1 67 1 0
#> 181.1 16.46 1 45 0 1
#> 89 11.44 1 NA 0 0
#> 88 18.37 1 47 0 0
#> 111.1 17.45 1 47 0 1
#> 166 19.98 1 48 0 0
#> 49.1 12.19 1 48 1 0
#> 68 20.62 1 44 0 0
#> 86 23.81 1 58 0 1
#> 180 14.82 1 37 0 0
#> 76 19.22 1 54 0 1
#> 177 12.53 1 75 0 0
#> 199 19.81 1 NA 0 1
#> 134 17.81 1 47 1 0
#> 140 12.68 1 59 1 0
#> 40 18.00 1 28 1 0
#> 114 13.68 1 NA 0 0
#> 66 22.13 1 53 0 0
#> 93 10.33 1 52 0 1
#> 149.1 8.37 1 33 1 0
#> 50.1 10.02 1 NA 1 0
#> 99 21.19 1 38 0 1
#> 188.1 16.16 1 46 0 1
#> 107.2 11.18 1 54 1 0
#> 10 10.53 1 34 0 0
#> 181.2 16.46 1 45 0 1
#> 113 22.86 1 34 0 0
#> 45 17.42 1 54 0 1
#> 175 21.91 1 43 0 0
#> 56.1 12.21 1 60 0 0
#> 110.1 17.56 1 65 0 1
#> 79 16.23 1 54 1 0
#> 60 13.15 1 38 1 0
#> 93.1 10.33 1 52 0 1
#> 59 10.16 1 NA 1 0
#> 124 9.73 1 NA 1 0
#> 195 11.76 1 NA 1 0
#> 168 23.72 1 70 0 0
#> 194 22.40 1 38 0 1
#> 86.1 23.81 1 58 0 1
#> 195.1 11.76 1 NA 1 0
#> 13 14.34 1 54 0 1
#> 16 8.71 1 71 0 1
#> 66.1 22.13 1 53 0 0
#> 37 12.52 1 57 1 0
#> 79.1 16.23 1 54 1 0
#> 101 9.97 1 10 0 1
#> 127 3.53 1 62 0 1
#> 6 15.64 1 39 0 0
#> 168.1 23.72 1 70 0 0
#> 136 21.83 1 43 0 1
#> 125 15.65 1 67 1 0
#> 99.1 21.19 1 38 0 1
#> 101.1 9.97 1 10 0 1
#> 57.1 14.46 1 45 0 1
#> 70 7.38 1 30 1 0
#> 32 20.90 1 37 1 0
#> 92 22.92 1 47 0 1
#> 117.2 17.46 1 26 0 1
#> 125.1 15.65 1 67 1 0
#> 10.1 10.53 1 34 0 0
#> 59.1 10.16 1 NA 1 0
#> 37.1 12.52 1 57 1 0
#> 167 15.55 1 56 1 0
#> 86.2 23.81 1 58 0 1
#> 79.2 16.23 1 54 1 0
#> 134.1 17.81 1 47 1 0
#> 128 20.35 1 35 0 1
#> 50.2 10.02 1 NA 1 0
#> 101.2 9.97 1 10 0 1
#> 157 15.10 1 47 0 0
#> 59.2 10.16 1 NA 1 0
#> 100 16.07 1 60 0 0
#> 105 19.75 1 60 0 0
#> 101.3 9.97 1 10 0 1
#> 184 17.77 1 38 0 0
#> 14 12.89 1 21 0 0
#> 63 22.77 1 31 1 0
#> 184.1 17.77 1 38 0 0
#> 158 20.14 1 74 1 0
#> 42 12.43 1 49 0 1
#> 18 15.21 1 49 1 0
#> 81.1 14.06 1 34 0 0
#> 93.2 10.33 1 52 0 1
#> 171 16.57 1 41 0 1
#> 158.1 20.14 1 74 1 0
#> 14.1 12.89 1 21 0 0
#> 99.2 21.19 1 38 0 1
#> 154 12.63 1 20 1 0
#> 159 10.55 1 50 0 1
#> 170 19.54 1 43 0 1
#> 173 24.00 0 19 0 1
#> 27 24.00 0 63 1 0
#> 151 24.00 0 42 0 0
#> 104 24.00 0 50 1 0
#> 119 24.00 0 17 0 0
#> 22 24.00 0 52 1 0
#> 74 24.00 0 43 0 1
#> 87 24.00 0 27 0 0
#> 7 24.00 0 37 1 0
#> 112 24.00 0 61 0 0
#> 161 24.00 0 45 0 0
#> 22.1 24.00 0 52 1 0
#> 116 24.00 0 58 0 1
#> 173.1 24.00 0 19 0 1
#> 98 24.00 0 34 1 0
#> 103 24.00 0 56 1 0
#> 109 24.00 0 48 0 0
#> 31 24.00 0 36 0 1
#> 22.2 24.00 0 52 1 0
#> 165 24.00 0 47 0 0
#> 119.1 24.00 0 17 0 0
#> 104.1 24.00 0 50 1 0
#> 11 24.00 0 42 0 1
#> 73 24.00 0 NA 0 1
#> 22.3 24.00 0 52 1 0
#> 131 24.00 0 66 0 0
#> 116.1 24.00 0 58 0 1
#> 185 24.00 0 44 1 0
#> 196 24.00 0 19 0 0
#> 193 24.00 0 45 0 1
#> 98.1 24.00 0 34 1 0
#> 48 24.00 0 31 1 0
#> 135 24.00 0 58 1 0
#> 200 24.00 0 64 0 0
#> 74.1 24.00 0 43 0 1
#> 27.1 24.00 0 63 1 0
#> 142 24.00 0 53 0 0
#> 147 24.00 0 76 1 0
#> 54 24.00 0 53 1 0
#> 3 24.00 0 31 1 0
#> 156 24.00 0 50 1 0
#> 80 24.00 0 41 0 0
#> 54.1 24.00 0 53 1 0
#> 82 24.00 0 34 0 0
#> 141 24.00 0 44 1 0
#> 48.1 24.00 0 31 1 0
#> 174 24.00 0 49 1 0
#> 198 24.00 0 66 0 1
#> 200.1 24.00 0 64 0 0
#> 156.1 24.00 0 50 1 0
#> 120 24.00 0 68 0 1
#> 160 24.00 0 31 1 0
#> 27.2 24.00 0 63 1 0
#> 38 24.00 0 31 1 0
#> 142.1 24.00 0 53 0 0
#> 178 24.00 0 52 1 0
#> 173.2 24.00 0 19 0 1
#> 74.2 24.00 0 43 0 1
#> 121 24.00 0 57 1 0
#> 3.1 24.00 0 31 1 0
#> 186 24.00 0 45 1 0
#> 74.3 24.00 0 43 0 1
#> 146 24.00 0 63 1 0
#> 53 24.00 0 32 0 1
#> 193.1 24.00 0 45 0 1
#> 94 24.00 0 51 0 1
#> 84 24.00 0 39 0 1
#> 165.1 24.00 0 47 0 0
#> 144 24.00 0 28 0 1
#> 54.2 24.00 0 53 1 0
#> 152 24.00 0 36 0 1
#> 20 24.00 0 46 1 0
#> 47 24.00 0 38 0 1
#> 121.1 24.00 0 57 1 0
#> 120.1 24.00 0 68 0 1
#> 54.3 24.00 0 53 1 0
#> 172 24.00 0 41 0 0
#> 121.2 24.00 0 57 1 0
#> 137 24.00 0 45 1 0
#> 137.1 24.00 0 45 1 0
#> 71 24.00 0 51 0 0
#> 17 24.00 0 38 0 1
#> 33 24.00 0 53 0 0
#> 3.2 24.00 0 31 1 0
#> 178.1 24.00 0 52 1 0
#> 172.1 24.00 0 41 0 0
#> 198.1 24.00 0 66 0 1
#> 176 24.00 0 43 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.246 NA NA NA
#> 2 age, Cure model 0.00930 NA NA NA
#> 3 grade_ii, Cure model -0.490 NA NA NA
#> 4 grade_iii, Cure model 0.400 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0170 NA NA NA
#> 2 grade_ii, Survival model 0.510 NA NA NA
#> 3 grade_iii, Survival model -0.0105 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.246236 0.009296 -0.490021 0.400470
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 258.3
#> Residual Deviance: 251.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.246235831 0.009295983 -0.490021337 0.400469757
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01696934 0.50960992 -0.01054740
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 1.735529e-01 2.359008e-02 4.293414e-01 6.531812e-01 6.083200e-01
#> [6] 6.531812e-01 1.498898e-01 9.644589e-01 1.345752e-01 9.338259e-02
#> [11] 3.913874e-01 2.087308e-01 6.379553e-01 9.124383e-01 8.609766e-01
#> [16] 3.317067e-01 5.790597e-01 2.664168e-01 2.082706e-03 1.498898e-01
#> [21] 8.609766e-01 2.087308e-01 8.670174e-02 1.735529e-01 6.275970e-02
#> [26] 6.083200e-01 4.317615e-02 4.355287e-05 3.791039e-01 8.029241e-02
#> [31] 5.228854e-01 1.068793e-01 4.955659e-01 1.001388e-01 1.161984e-02
#> [36] 7.464105e-01 9.124383e-01 2.725243e-02 2.664168e-01 6.531812e-01
#> [41] 7.146137e-01 2.087308e-01 5.186433e-03 1.905902e-01 1.692800e-02
#> [46] 5.790597e-01 1.345752e-01 2.369860e-01 4.555118e-01 7.464105e-01
#> [51] 6.507174e-04 9.305306e-03 4.355287e-05 4.164020e-01 8.950176e-01
#> [56] 1.161984e-02 5.367717e-01 2.369860e-01 7.954241e-01 9.821242e-01
#> [61] 3.202616e-01 6.507174e-04 2.011476e-02 2.981560e-01 2.725243e-02
#> [66] 7.954241e-01 3.913874e-01 9.470117e-01 3.880800e-02 3.441008e-03
#> [71] 1.498898e-01 2.981560e-01 7.146137e-01 5.367717e-01 3.433412e-01
#> [76] 4.355287e-05 2.369860e-01 1.068793e-01 4.779005e-02 7.954241e-01
#> [81] 3.670032e-01 2.872738e-01 6.831658e-02 7.954241e-01 1.203484e-01
#> [86] 4.688397e-01 7.239091e-03 1.203484e-01 5.261550e-02 5.647091e-01
#> [91] 3.551180e-01 4.293414e-01 7.464105e-01 1.995561e-01 5.261550e-02
#> [96] 4.688397e-01 2.725243e-02 5.092597e-01 6.988457e-01 7.417809e-02
#> [101] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [106] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [186] 0.000000e+00 0.000000e+00
#>
#> $Time
#> 111 153 81 107 49 107.1 117 77 110 41 57 181 43
#> 17.45 21.33 14.06 11.18 12.19 11.18 17.46 7.27 17.56 18.02 14.46 16.46 12.10
#> 149 183 39 56 188 164 117.1 183.1 181.1 88 111.1 166 49.1
#> 8.37 9.24 15.59 12.21 16.16 23.60 17.46 9.24 16.46 18.37 17.45 19.98 12.19
#> 68 86 180 76 177 134 140 40 66 93 149.1 99 188.1
#> 20.62 23.81 14.82 19.22 12.53 17.81 12.68 18.00 22.13 10.33 8.37 21.19 16.16
#> 107.2 10 181.2 113 45 175 56.1 110.1 79 60 93.1 168 194
#> 11.18 10.53 16.46 22.86 17.42 21.91 12.21 17.56 16.23 13.15 10.33 23.72 22.40
#> 86.1 13 16 66.1 37 79.1 101 127 6 168.1 136 125 99.1
#> 23.81 14.34 8.71 22.13 12.52 16.23 9.97 3.53 15.64 23.72 21.83 15.65 21.19
#> 101.1 57.1 70 32 92 117.2 125.1 10.1 37.1 167 86.2 79.2 134.1
#> 9.97 14.46 7.38 20.90 22.92 17.46 15.65 10.53 12.52 15.55 23.81 16.23 17.81
#> 128 101.2 157 100 105 101.3 184 14 63 184.1 158 42 18
#> 20.35 9.97 15.10 16.07 19.75 9.97 17.77 12.89 22.77 17.77 20.14 12.43 15.21
#> 81.1 93.2 171 158.1 14.1 99.2 154 159 170 173 27 151 104
#> 14.06 10.33 16.57 20.14 12.89 21.19 12.63 10.55 19.54 24.00 24.00 24.00 24.00
#> 119 22 74 87 7 112 161 22.1 116 173.1 98 103 109
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31 22.2 165 119.1 104.1 11 22.3 131 116.1 185 196 193 98.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 48 135 200 74.1 27.1 142 147 54 3 156 80 54.1 82
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 141 48.1 174 198 200.1 156.1 120 160 27.2 38 142.1 178 173.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 74.2 121 3.1 186 74.3 146 53 193.1 94 84 165.1 144 54.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152 20 47 121.1 120.1 54.3 172 121.2 137 137.1 71 17 33
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3.2 178.1 172.1 198.1 176
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[15]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01061897 0.76782630 0.34313123
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.308320484 -0.005171354 0.133031928
#> grade_iii, Cure model
#> 0.313464720
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 97 19.14 1 65 0 1
#> 140 12.68 1 59 1 0
#> 133 14.65 1 57 0 0
#> 88 18.37 1 47 0 0
#> 164 23.60 1 76 0 1
#> 4 17.64 1 NA 0 1
#> 128 20.35 1 35 0 1
#> 78 23.88 1 43 0 0
#> 170 19.54 1 43 0 1
#> 166 19.98 1 48 0 0
#> 140.1 12.68 1 59 1 0
#> 8 18.43 1 32 0 0
#> 70 7.38 1 30 1 0
#> 113 22.86 1 34 0 0
#> 125 15.65 1 67 1 0
#> 106 16.67 1 49 1 0
#> 18 15.21 1 49 1 0
#> 10 10.53 1 34 0 0
#> 24 23.89 1 38 0 0
#> 149 8.37 1 33 1 0
#> 129 23.41 1 53 1 0
#> 16 8.71 1 71 0 1
#> 179 18.63 1 42 0 0
#> 37 12.52 1 57 1 0
#> 105 19.75 1 60 0 0
#> 180 14.82 1 37 0 0
#> 6 15.64 1 39 0 0
#> 197 21.60 1 69 1 0
#> 139 21.49 1 63 1 0
#> 170.1 19.54 1 43 0 1
#> 134 17.81 1 47 1 0
#> 99 21.19 1 38 0 1
#> 150 20.33 1 48 0 0
#> 179.1 18.63 1 42 0 0
#> 114 13.68 1 NA 0 0
#> 158 20.14 1 74 1 0
#> 10.1 10.53 1 34 0 0
#> 149.1 8.37 1 33 1 0
#> 114.1 13.68 1 NA 0 0
#> 128.1 20.35 1 35 0 1
#> 155 13.08 1 26 0 0
#> 32 20.90 1 37 1 0
#> 179.2 18.63 1 42 0 0
#> 170.2 19.54 1 43 0 1
#> 153 21.33 1 55 1 0
#> 59 10.16 1 NA 1 0
#> 30 17.43 1 78 0 0
#> 106.1 16.67 1 49 1 0
#> 155.1 13.08 1 26 0 0
#> 57 14.46 1 45 0 1
#> 123 13.00 1 44 1 0
#> 32.1 20.90 1 37 1 0
#> 92 22.92 1 47 0 1
#> 42 12.43 1 49 0 1
#> 5 16.43 1 51 0 1
#> 79 16.23 1 54 1 0
#> 29 15.45 1 68 1 0
#> 181 16.46 1 45 0 1
#> 93 10.33 1 52 0 1
#> 14 12.89 1 21 0 0
#> 14.1 12.89 1 21 0 0
#> 100 16.07 1 60 0 0
#> 77 7.27 1 67 0 1
#> 195 11.76 1 NA 1 0
#> 180.1 14.82 1 37 0 0
#> 68 20.62 1 44 0 0
#> 63 22.77 1 31 1 0
#> 175 21.91 1 43 0 0
#> 93.1 10.33 1 52 0 1
#> 190 20.81 1 42 1 0
#> 68.1 20.62 1 44 0 0
#> 68.2 20.62 1 44 0 0
#> 134.1 17.81 1 47 1 0
#> 78.1 23.88 1 43 0 0
#> 81 14.06 1 34 0 0
#> 113.1 22.86 1 34 0 0
#> 194 22.40 1 38 0 1
#> 124 9.73 1 NA 1 0
#> 108 18.29 1 39 0 1
#> 69 23.23 1 25 0 1
#> 107 11.18 1 54 1 0
#> 100.1 16.07 1 60 0 0
#> 180.2 14.82 1 37 0 0
#> 189 10.51 1 NA 1 0
#> 168 23.72 1 70 0 0
#> 187 9.92 1 39 1 0
#> 93.2 10.33 1 52 0 1
#> 164.1 23.60 1 76 0 1
#> 192 16.44 1 31 1 0
#> 78.2 23.88 1 43 0 0
#> 70.1 7.38 1 30 1 0
#> 86 23.81 1 58 0 1
#> 124.1 9.73 1 NA 1 0
#> 134.2 17.81 1 47 1 0
#> 24.1 23.89 1 38 0 0
#> 40 18.00 1 28 1 0
#> 136 21.83 1 43 0 1
#> 164.2 23.60 1 76 0 1
#> 171 16.57 1 41 0 1
#> 5.1 16.43 1 51 0 1
#> 40.1 18.00 1 28 1 0
#> 78.3 23.88 1 43 0 0
#> 43 12.10 1 61 0 1
#> 36 21.19 1 48 0 1
#> 187.1 9.92 1 39 1 0
#> 58 19.34 1 39 0 0
#> 108.1 18.29 1 39 0 1
#> 111 17.45 1 47 0 1
#> 6.1 15.64 1 39 0 0
#> 134.3 17.81 1 47 1 0
#> 70.2 7.38 1 30 1 0
#> 39 15.59 1 37 0 1
#> 185 24.00 0 44 1 0
#> 144 24.00 0 28 0 1
#> 176 24.00 0 43 0 1
#> 82 24.00 0 34 0 0
#> 75 24.00 0 21 1 0
#> 84 24.00 0 39 0 1
#> 176.1 24.00 0 43 0 1
#> 44 24.00 0 56 0 0
#> 21 24.00 0 47 0 0
#> 146 24.00 0 63 1 0
#> 20 24.00 0 46 1 0
#> 126 24.00 0 48 0 0
#> 31 24.00 0 36 0 1
#> 54 24.00 0 53 1 0
#> 64 24.00 0 43 0 0
#> 73 24.00 0 NA 0 1
#> 152 24.00 0 36 0 1
#> 142 24.00 0 53 0 0
#> 38 24.00 0 31 1 0
#> 191 24.00 0 60 0 1
#> 161 24.00 0 45 0 0
#> 131 24.00 0 66 0 0
#> 176.2 24.00 0 43 0 1
#> 174 24.00 0 49 1 0
#> 191.1 24.00 0 60 0 1
#> 182 24.00 0 35 0 0
#> 73.1 24.00 0 NA 0 1
#> 122 24.00 0 66 0 0
#> 193 24.00 0 45 0 1
#> 94 24.00 0 51 0 1
#> 98 24.00 0 34 1 0
#> 34 24.00 0 36 0 0
#> 33 24.00 0 53 0 0
#> 196 24.00 0 19 0 0
#> 141 24.00 0 44 1 0
#> 148 24.00 0 61 1 0
#> 118 24.00 0 44 1 0
#> 193.1 24.00 0 45 0 1
#> 35 24.00 0 51 0 0
#> 182.1 24.00 0 35 0 0
#> 87 24.00 0 27 0 0
#> 141.1 24.00 0 44 1 0
#> 151 24.00 0 42 0 0
#> 65 24.00 0 57 1 0
#> 156 24.00 0 50 1 0
#> 132 24.00 0 55 0 0
#> 160 24.00 0 31 1 0
#> 11 24.00 0 42 0 1
#> 64.1 24.00 0 43 0 0
#> 74 24.00 0 43 0 1
#> 120 24.00 0 68 0 1
#> 64.2 24.00 0 43 0 0
#> 196.1 24.00 0 19 0 0
#> 35.1 24.00 0 51 0 0
#> 62 24.00 0 71 0 0
#> 115 24.00 0 NA 1 0
#> 27 24.00 0 63 1 0
#> 119 24.00 0 17 0 0
#> 28 24.00 0 67 1 0
#> 137 24.00 0 45 1 0
#> 173 24.00 0 19 0 1
#> 84.1 24.00 0 39 0 1
#> 1 24.00 0 23 1 0
#> 65.1 24.00 0 57 1 0
#> 118.1 24.00 0 44 1 0
#> 112 24.00 0 61 0 0
#> 103 24.00 0 56 1 0
#> 21.1 24.00 0 47 0 0
#> 33.1 24.00 0 53 0 0
#> 31.1 24.00 0 36 0 1
#> 11.1 24.00 0 42 0 1
#> 109 24.00 0 48 0 0
#> 28.1 24.00 0 67 1 0
#> 147 24.00 0 76 1 0
#> 62.1 24.00 0 71 0 0
#> 148.1 24.00 0 61 1 0
#> 156.1 24.00 0 50 1 0
#> 102 24.00 0 49 0 0
#> 163 24.00 0 66 0 0
#> 65.2 24.00 0 57 1 0
#> 31.2 24.00 0 36 0 1
#> 198 24.00 0 66 0 1
#> 151.1 24.00 0 42 0 0
#> 67 24.00 0 25 0 0
#> 138 24.00 0 44 1 0
#> 2 24.00 0 9 0 0
#> 12 24.00 0 63 0 0
#> 95 24.00 0 68 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.308 NA NA NA
#> 2 age, Cure model -0.00517 NA NA NA
#> 3 grade_ii, Cure model 0.133 NA NA NA
#> 4 grade_iii, Cure model 0.313 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0106 NA NA NA
#> 2 grade_ii, Survival model 0.768 NA NA NA
#> 3 grade_iii, Survival model 0.343 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.308320 -0.005171 0.133032 0.313465
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.1
#> Residual Deviance: 259.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.308320484 -0.005171354 0.133031928 0.313464720
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01061897 0.76782630 0.34313123
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.354141947 0.791214064 0.707480860 0.405049507 0.046558672 0.258009709
#> [7] 0.010970914 0.315229118 0.295690828 0.791214064 0.394584261 0.959188497
#> [13] 0.099219941 0.615752477 0.515866137 0.666701249 0.854137119 0.002455084
#> [19] 0.938365515 0.071501696 0.927773183 0.364239533 0.812094070 0.305386343
#> [25] 0.676900191 0.625885174 0.156084626 0.165773569 0.315229118 0.456932511
#> [31] 0.184929505 0.276556181 0.364239533 0.286120640 0.854137119 0.938365515
#> [37] 0.258009709 0.738804080 0.203690520 0.364239533 0.315229118 0.175404217
#> [43] 0.505731423 0.515866137 0.738804080 0.717894055 0.759753363 0.203690520
#> [49] 0.089916598 0.822578116 0.565778158 0.585649862 0.656458309 0.545756707
#> [55] 0.875188856 0.770250126 0.770250126 0.595634800 0.989692677 0.676900191
#> [61] 0.230750987 0.117976937 0.136732881 0.875188856 0.221698691 0.230750987
#> [67] 0.230750987 0.456932511 0.010970914 0.728326326 0.099219941 0.127334524
#> [73] 0.415622094 0.080750917 0.843624604 0.595634800 0.676900191 0.038278231
#> [79] 0.906789699 0.875188856 0.046558672 0.555817064 0.010970914 0.959188497
#> [85] 0.030843936 0.456932511 0.002455084 0.436570656 0.146374341 0.046558672
#> [91] 0.535719674 0.565778158 0.436570656 0.010970914 0.833083906 0.184929505
#> [97] 0.906789699 0.344128110 0.415622094 0.495709820 0.625885174 0.456932511
#> [103] 0.959188497 0.646207887 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 97 140 133 88 164 128 78 170 166 140.1 8 70 113
#> 19.14 12.68 14.65 18.37 23.60 20.35 23.88 19.54 19.98 12.68 18.43 7.38 22.86
#> 125 106 18 10 24 149 129 16 179 37 105 180 6
#> 15.65 16.67 15.21 10.53 23.89 8.37 23.41 8.71 18.63 12.52 19.75 14.82 15.64
#> 197 139 170.1 134 99 150 179.1 158 10.1 149.1 128.1 155 32
#> 21.60 21.49 19.54 17.81 21.19 20.33 18.63 20.14 10.53 8.37 20.35 13.08 20.90
#> 179.2 170.2 153 30 106.1 155.1 57 123 32.1 92 42 5 79
#> 18.63 19.54 21.33 17.43 16.67 13.08 14.46 13.00 20.90 22.92 12.43 16.43 16.23
#> 29 181 93 14 14.1 100 77 180.1 68 63 175 93.1 190
#> 15.45 16.46 10.33 12.89 12.89 16.07 7.27 14.82 20.62 22.77 21.91 10.33 20.81
#> 68.1 68.2 134.1 78.1 81 113.1 194 108 69 107 100.1 180.2 168
#> 20.62 20.62 17.81 23.88 14.06 22.86 22.40 18.29 23.23 11.18 16.07 14.82 23.72
#> 187 93.2 164.1 192 78.2 70.1 86 134.2 24.1 40 136 164.2 171
#> 9.92 10.33 23.60 16.44 23.88 7.38 23.81 17.81 23.89 18.00 21.83 23.60 16.57
#> 5.1 40.1 78.3 43 36 187.1 58 108.1 111 6.1 134.3 70.2 39
#> 16.43 18.00 23.88 12.10 21.19 9.92 19.34 18.29 17.45 15.64 17.81 7.38 15.59
#> 185 144 176 82 75 84 176.1 44 21 146 20 126 31
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 54 64 152 142 38 191 161 131 176.2 174 191.1 182 122
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193 94 98 34 33 196 141 148 118 193.1 35 182.1 87
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 141.1 151 65 156 132 160 11 64.1 74 120 64.2 196.1 35.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62 27 119 28 137 173 84.1 1 65.1 118.1 112 103 21.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33.1 31.1 11.1 109 28.1 147 62.1 148.1 156.1 102 163 65.2 31.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 198 151.1 67 138 2 12 95
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[16]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.007116192 0.232734882 0.397192063
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.289461962 -0.007120419 -0.350298304
#> grade_iii, Cure model
#> 1.120152473
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 105 19.75 1 60 0 0
#> 150 20.33 1 48 0 0
#> 164 23.60 1 76 0 1
#> 42 12.43 1 49 0 1
#> 113 22.86 1 34 0 0
#> 61 10.12 1 36 0 1
#> 93 10.33 1 52 0 1
#> 52 10.42 1 52 0 1
#> 157 15.10 1 47 0 0
#> 179 18.63 1 42 0 0
#> 123 13.00 1 44 1 0
#> 4 17.64 1 NA 0 1
#> 180 14.82 1 37 0 0
#> 14 12.89 1 21 0 0
#> 57 14.46 1 45 0 1
#> 50 10.02 1 NA 1 0
#> 8 18.43 1 32 0 0
#> 129 23.41 1 53 1 0
#> 157.1 15.10 1 47 0 0
#> 149 8.37 1 33 1 0
#> 78 23.88 1 43 0 0
#> 51 18.23 1 83 0 1
#> 149.1 8.37 1 33 1 0
#> 13 14.34 1 54 0 1
#> 90 20.94 1 50 0 1
#> 166 19.98 1 48 0 0
#> 149.2 8.37 1 33 1 0
#> 92 22.92 1 47 0 1
#> 184 17.77 1 38 0 0
#> 52.1 10.42 1 52 0 1
#> 181 16.46 1 45 0 1
#> 15 22.68 1 48 0 0
#> 111 17.45 1 47 0 1
#> 77 7.27 1 67 0 1
#> 177 12.53 1 75 0 0
#> 164.1 23.60 1 76 0 1
#> 41 18.02 1 40 1 0
#> 97 19.14 1 65 0 1
#> 10 10.53 1 34 0 0
#> 101 9.97 1 10 0 1
#> 155 13.08 1 26 0 0
#> 69 23.23 1 25 0 1
#> 41.1 18.02 1 40 1 0
#> 81 14.06 1 34 0 0
#> 187 9.92 1 39 1 0
#> 179.1 18.63 1 42 0 0
#> 36 21.19 1 48 0 1
#> 24 23.89 1 38 0 0
#> 76 19.22 1 54 0 1
#> 180.1 14.82 1 37 0 0
#> 42.1 12.43 1 49 0 1
#> 114 13.68 1 NA 0 0
#> 155.1 13.08 1 26 0 0
#> 50.1 10.02 1 NA 1 0
#> 179.2 18.63 1 42 0 0
#> 57.1 14.46 1 45 0 1
#> 93.1 10.33 1 52 0 1
#> 154 12.63 1 20 1 0
#> 170 19.54 1 43 0 1
#> 6 15.64 1 39 0 0
#> 50.2 10.02 1 NA 1 0
#> 111.1 17.45 1 47 0 1
#> 61.1 10.12 1 36 0 1
#> 85 16.44 1 36 0 0
#> 175 21.91 1 43 0 0
#> 69.1 23.23 1 25 0 1
#> 113.1 22.86 1 34 0 0
#> 51.1 18.23 1 83 0 1
#> 43 12.10 1 61 0 1
#> 194 22.40 1 38 0 1
#> 133 14.65 1 57 0 0
#> 40 18.00 1 28 1 0
#> 190 20.81 1 42 1 0
#> 15.1 22.68 1 48 0 0
#> 52.2 10.42 1 52 0 1
#> 177.1 12.53 1 75 0 0
#> 107 11.18 1 54 1 0
#> 56 12.21 1 60 0 0
#> 96 14.54 1 33 0 1
#> 188 16.16 1 46 0 1
#> 97.1 19.14 1 65 0 1
#> 26 15.77 1 49 0 1
#> 189 10.51 1 NA 1 0
#> 86 23.81 1 58 0 1
#> 49 12.19 1 48 1 0
#> 77.1 7.27 1 67 0 1
#> 180.2 14.82 1 37 0 0
#> 37 12.52 1 57 1 0
#> 108 18.29 1 39 0 1
#> 77.2 7.27 1 67 0 1
#> 197 21.60 1 69 1 0
#> 180.3 14.82 1 37 0 0
#> 128 20.35 1 35 0 1
#> 113.2 22.86 1 34 0 0
#> 159 10.55 1 50 0 1
#> 42.2 12.43 1 49 0 1
#> 169 22.41 1 46 0 0
#> 157.2 15.10 1 47 0 0
#> 153 21.33 1 55 1 0
#> 93.2 10.33 1 52 0 1
#> 4.1 17.64 1 NA 0 1
#> 199 19.81 1 NA 0 1
#> 113.3 22.86 1 34 0 0
#> 175.1 21.91 1 43 0 0
#> 124 9.73 1 NA 1 0
#> 129.1 23.41 1 53 1 0
#> 129.2 23.41 1 53 1 0
#> 63 22.77 1 31 1 0
#> 26.1 15.77 1 49 0 1
#> 93.3 10.33 1 52 0 1
#> 111.2 17.45 1 47 0 1
#> 15.2 22.68 1 48 0 0
#> 138 24.00 0 44 1 0
#> 35 24.00 0 51 0 0
#> 80 24.00 0 41 0 0
#> 196 24.00 0 19 0 0
#> 163 24.00 0 66 0 0
#> 193 24.00 0 45 0 1
#> 27 24.00 0 63 1 0
#> 185 24.00 0 44 1 0
#> 142 24.00 0 53 0 0
#> 73 24.00 0 NA 0 1
#> 142.1 24.00 0 53 0 0
#> 17 24.00 0 38 0 1
#> 75 24.00 0 21 1 0
#> 143 24.00 0 51 0 0
#> 12 24.00 0 63 0 0
#> 141 24.00 0 44 1 0
#> 48 24.00 0 31 1 0
#> 200 24.00 0 64 0 0
#> 118 24.00 0 44 1 0
#> 120 24.00 0 68 0 1
#> 67 24.00 0 25 0 0
#> 7 24.00 0 37 1 0
#> 126 24.00 0 48 0 0
#> 165 24.00 0 47 0 0
#> 119 24.00 0 17 0 0
#> 120.1 24.00 0 68 0 1
#> 115 24.00 0 NA 1 0
#> 112 24.00 0 61 0 0
#> 116 24.00 0 58 0 1
#> 115.1 24.00 0 NA 1 0
#> 172 24.00 0 41 0 0
#> 118.1 24.00 0 44 1 0
#> 146 24.00 0 63 1 0
#> 173 24.00 0 19 0 1
#> 44 24.00 0 56 0 0
#> 46 24.00 0 71 0 0
#> 163.1 24.00 0 66 0 0
#> 156 24.00 0 50 1 0
#> 65 24.00 0 57 1 0
#> 152 24.00 0 36 0 1
#> 176 24.00 0 43 0 1
#> 163.2 24.00 0 66 0 0
#> 62 24.00 0 71 0 0
#> 185.1 24.00 0 44 1 0
#> 137 24.00 0 45 1 0
#> 120.2 24.00 0 68 0 1
#> 182 24.00 0 35 0 0
#> 53 24.00 0 32 0 1
#> 62.1 24.00 0 71 0 0
#> 7.1 24.00 0 37 1 0
#> 72 24.00 0 40 0 1
#> 178 24.00 0 52 1 0
#> 182.1 24.00 0 35 0 0
#> 200.1 24.00 0 64 0 0
#> 64 24.00 0 43 0 0
#> 7.2 24.00 0 37 1 0
#> 62.2 24.00 0 71 0 0
#> 87 24.00 0 27 0 0
#> 54 24.00 0 53 1 0
#> 115.2 24.00 0 NA 1 0
#> 64.1 24.00 0 43 0 0
#> 196.1 24.00 0 19 0 0
#> 104 24.00 0 50 1 0
#> 122 24.00 0 66 0 0
#> 135 24.00 0 58 1 0
#> 103 24.00 0 56 1 0
#> 151 24.00 0 42 0 0
#> 152.1 24.00 0 36 0 1
#> 119.1 24.00 0 17 0 0
#> 62.3 24.00 0 71 0 0
#> 82 24.00 0 34 0 0
#> 7.3 24.00 0 37 1 0
#> 2 24.00 0 9 0 0
#> 116.1 24.00 0 58 0 1
#> 27.1 24.00 0 63 1 0
#> 7.4 24.00 0 37 1 0
#> 196.2 24.00 0 19 0 0
#> 84 24.00 0 39 0 1
#> 11 24.00 0 42 0 1
#> 146.1 24.00 0 63 1 0
#> 103.1 24.00 0 56 1 0
#> 143.1 24.00 0 51 0 0
#> 83 24.00 0 6 0 0
#> 135.1 24.00 0 58 1 0
#> 174 24.00 0 49 1 0
#> 193.1 24.00 0 45 0 1
#> 115.3 24.00 0 NA 1 0
#> 151.1 24.00 0 42 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.289 NA NA NA
#> 2 age, Cure model -0.00712 NA NA NA
#> 3 grade_ii, Cure model -0.350 NA NA NA
#> 4 grade_iii, Cure model 1.12 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00712 NA NA NA
#> 2 grade_ii, Survival model 0.233 NA NA NA
#> 3 grade_iii, Survival model 0.397 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.28946 -0.00712 -0.35030 1.12015
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 255.7
#> Residual Deviance: 240.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.289461962 -0.007120419 -0.350298304 1.120152473
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.007116192 0.232734882 0.397192063
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.264730307 0.245736791 0.026082086 0.726051095 0.088885122 0.894891821
#> [7] 0.853007238 0.821354210 0.509941465 0.312695833 0.663030660 0.539944176
#> [13] 0.673482543 0.601054996 0.341467241 0.041912496 0.509941465 0.937160819
#> [19] 0.008951006 0.361295086 0.937160819 0.621583624 0.217618137 0.255182404
#> [25] 0.937160819 0.080712638 0.410761309 0.821354210 0.450133368 0.128037359
#> [31] 0.420816055 0.968541378 0.694416288 0.026082086 0.381003855 0.293668674
#> [37] 0.810653238 0.916009358 0.642316682 0.065099657 0.381003855 0.631931878
#> [43] 0.926582444 0.312695833 0.208225070 0.002413933 0.284036158 0.539944176
#> [49] 0.726051095 0.642316682 0.312695833 0.601054996 0.853007238 0.683956992
#> [55] 0.274399425 0.499909118 0.420816055 0.894891821 0.460108288 0.171410541
#> [61] 0.065099657 0.088885122 0.361295086 0.778649383 0.162395170 0.580258604
#> [67] 0.400764553 0.226994170 0.128037359 0.821354210 0.694416288 0.789305826
#> [73] 0.757362277 0.590672931 0.470132327 0.293668674 0.480140937 0.017438429
#> [79] 0.767998223 0.968541378 0.539944176 0.715437290 0.351398930 0.968541378
#> [85] 0.189455562 0.539944176 0.236395109 0.088885122 0.799982540 0.726051095
#> [91] 0.153311789 0.509941465 0.198807784 0.853007238 0.088885122 0.171410541
#> [97] 0.041912496 0.041912496 0.119516551 0.480140937 0.853007238 0.420816055
#> [103] 0.128037359 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 105 150 164 42 113 61 93 52 157 179 123 180 14
#> 19.75 20.33 23.60 12.43 22.86 10.12 10.33 10.42 15.10 18.63 13.00 14.82 12.89
#> 57 8 129 157.1 149 78 51 149.1 13 90 166 149.2 92
#> 14.46 18.43 23.41 15.10 8.37 23.88 18.23 8.37 14.34 20.94 19.98 8.37 22.92
#> 184 52.1 181 15 111 77 177 164.1 41 97 10 101 155
#> 17.77 10.42 16.46 22.68 17.45 7.27 12.53 23.60 18.02 19.14 10.53 9.97 13.08
#> 69 41.1 81 187 179.1 36 24 76 180.1 42.1 155.1 179.2 57.1
#> 23.23 18.02 14.06 9.92 18.63 21.19 23.89 19.22 14.82 12.43 13.08 18.63 14.46
#> 93.1 154 170 6 111.1 61.1 85 175 69.1 113.1 51.1 43 194
#> 10.33 12.63 19.54 15.64 17.45 10.12 16.44 21.91 23.23 22.86 18.23 12.10 22.40
#> 133 40 190 15.1 52.2 177.1 107 56 96 188 97.1 26 86
#> 14.65 18.00 20.81 22.68 10.42 12.53 11.18 12.21 14.54 16.16 19.14 15.77 23.81
#> 49 77.1 180.2 37 108 77.2 197 180.3 128 113.2 159 42.2 169
#> 12.19 7.27 14.82 12.52 18.29 7.27 21.60 14.82 20.35 22.86 10.55 12.43 22.41
#> 157.2 153 93.2 113.3 175.1 129.1 129.2 63 26.1 93.3 111.2 15.2 138
#> 15.10 21.33 10.33 22.86 21.91 23.41 23.41 22.77 15.77 10.33 17.45 22.68 24.00
#> 35 80 196 163 193 27 185 142 142.1 17 75 143 12
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 141 48 200 118 120 67 7 126 165 119 120.1 112 116
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172 118.1 146 173 44 46 163.1 156 65 152 176 163.2 62
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185.1 137 120.2 182 53 62.1 7.1 72 178 182.1 200.1 64 7.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62.2 87 54 64.1 196.1 104 122 135 103 151 152.1 119.1 62.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 82 7.3 2 116.1 27.1 7.4 196.2 84 11 146.1 103.1 143.1 83
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135.1 174 193.1 151.1
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[17]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01045353 0.85713482 0.11069606
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.09609759 0.01741399 0.44485621
#> grade_iii, Cure model
#> 1.00551626
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 86 23.81 1 58 0 1
#> 154 12.63 1 20 1 0
#> 171 16.57 1 41 0 1
#> 85 16.44 1 36 0 0
#> 167 15.55 1 56 1 0
#> 111 17.45 1 47 0 1
#> 130 16.47 1 53 0 1
#> 169 22.41 1 46 0 0
#> 5 16.43 1 51 0 1
#> 16 8.71 1 71 0 1
#> 79 16.23 1 54 1 0
#> 127 3.53 1 62 0 1
#> 66 22.13 1 53 0 0
#> 125 15.65 1 67 1 0
#> 199 19.81 1 NA 0 1
#> 134 17.81 1 47 1 0
#> 52 10.42 1 52 0 1
#> 76 19.22 1 54 0 1
#> 171.1 16.57 1 41 0 1
#> 168 23.72 1 70 0 0
#> 29 15.45 1 68 1 0
#> 86.1 23.81 1 58 0 1
#> 127.1 3.53 1 62 0 1
#> 81 14.06 1 34 0 0
#> 107 11.18 1 54 1 0
#> 136 21.83 1 43 0 1
#> 149 8.37 1 33 1 0
#> 171.2 16.57 1 41 0 1
#> 164 23.60 1 76 0 1
#> 181 16.46 1 45 0 1
#> 15 22.68 1 48 0 0
#> 108 18.29 1 39 0 1
#> 49 12.19 1 48 1 0
#> 57 14.46 1 45 0 1
#> 25 6.32 1 34 1 0
#> 101 9.97 1 10 0 1
#> 136.1 21.83 1 43 0 1
#> 5.1 16.43 1 51 0 1
#> 129 23.41 1 53 1 0
#> 14 12.89 1 21 0 0
#> 18 15.21 1 49 1 0
#> 153 21.33 1 55 1 0
#> 92 22.92 1 47 0 1
#> 15.1 22.68 1 48 0 0
#> 61 10.12 1 36 0 1
#> 51 18.23 1 83 0 1
#> 8 18.43 1 32 0 0
#> 90 20.94 1 50 0 1
#> 197 21.60 1 69 1 0
#> 140 12.68 1 59 1 0
#> 192 16.44 1 31 1 0
#> 157 15.10 1 47 0 0
#> 23 16.92 1 61 0 0
#> 59 10.16 1 NA 1 0
#> 166 19.98 1 48 0 0
#> 155 13.08 1 26 0 0
#> 124 9.73 1 NA 1 0
#> 107.1 11.18 1 54 1 0
#> 24 23.89 1 38 0 0
#> 194 22.40 1 38 0 1
#> 50 10.02 1 NA 1 0
#> 58 19.34 1 39 0 0
#> 154.1 12.63 1 20 1 0
#> 79.1 16.23 1 54 1 0
#> 153.1 21.33 1 55 1 0
#> 79.2 16.23 1 54 1 0
#> 99 21.19 1 38 0 1
#> 96 14.54 1 33 0 1
#> 26 15.77 1 49 0 1
#> 29.1 15.45 1 68 1 0
#> 179 18.63 1 42 0 0
#> 108.1 18.29 1 39 0 1
#> 170 19.54 1 43 0 1
#> 92.1 22.92 1 47 0 1
#> 136.2 21.83 1 43 0 1
#> 14.1 12.89 1 21 0 0
#> 97 19.14 1 65 0 1
#> 167.1 15.55 1 56 1 0
#> 69 23.23 1 25 0 1
#> 180 14.82 1 37 0 0
#> 123 13.00 1 44 1 0
#> 50.1 10.02 1 NA 1 0
#> 63 22.77 1 31 1 0
#> 36 21.19 1 48 0 1
#> 51.1 18.23 1 83 0 1
#> 107.2 11.18 1 54 1 0
#> 89 11.44 1 NA 0 0
#> 125.1 15.65 1 67 1 0
#> 158 20.14 1 74 1 0
#> 167.2 15.55 1 56 1 0
#> 166.1 19.98 1 48 0 0
#> 58.1 19.34 1 39 0 0
#> 42 12.43 1 49 0 1
#> 23.1 16.92 1 61 0 0
#> 194.1 22.40 1 38 0 1
#> 123.1 13.00 1 44 1 0
#> 168.1 23.72 1 70 0 0
#> 56 12.21 1 60 0 0
#> 77 7.27 1 67 0 1
#> 140.1 12.68 1 59 1 0
#> 157.1 15.10 1 47 0 0
#> 179.1 18.63 1 42 0 0
#> 194.2 22.40 1 38 0 1
#> 66.1 22.13 1 53 0 0
#> 40 18.00 1 28 1 0
#> 167.3 15.55 1 56 1 0
#> 105 19.75 1 60 0 0
#> 189 10.51 1 NA 1 0
#> 187 9.92 1 39 1 0
#> 125.2 15.65 1 67 1 0
#> 145 10.07 1 65 1 0
#> 124.1 9.73 1 NA 1 0
#> 83 24.00 0 6 0 0
#> 22 24.00 0 52 1 0
#> 64 24.00 0 43 0 0
#> 182 24.00 0 35 0 0
#> 20 24.00 0 46 1 0
#> 112 24.00 0 61 0 0
#> 163 24.00 0 66 0 0
#> 172 24.00 0 41 0 0
#> 103 24.00 0 56 1 0
#> 87 24.00 0 27 0 0
#> 151 24.00 0 42 0 0
#> 54 24.00 0 53 1 0
#> 193 24.00 0 45 0 1
#> 165 24.00 0 47 0 0
#> 3 24.00 0 31 1 0
#> 142 24.00 0 53 0 0
#> 38 24.00 0 31 1 0
#> 156 24.00 0 50 1 0
#> 172.1 24.00 0 41 0 0
#> 94 24.00 0 51 0 1
#> 9 24.00 0 31 1 0
#> 20.1 24.00 0 46 1 0
#> 72 24.00 0 40 0 1
#> 54.1 24.00 0 53 1 0
#> 163.1 24.00 0 66 0 0
#> 38.1 24.00 0 31 1 0
#> 75 24.00 0 21 1 0
#> 144 24.00 0 28 0 1
#> 3.1 24.00 0 31 1 0
#> 64.1 24.00 0 43 0 0
#> 132 24.00 0 55 0 0
#> 28 24.00 0 67 1 0
#> 83.1 24.00 0 6 0 0
#> 28.1 24.00 0 67 1 0
#> 65 24.00 0 57 1 0
#> 31 24.00 0 36 0 1
#> 182.1 24.00 0 35 0 0
#> 1 24.00 0 23 1 0
#> 7 24.00 0 37 1 0
#> 94.1 24.00 0 51 0 1
#> 17 24.00 0 38 0 1
#> 82 24.00 0 34 0 0
#> 137 24.00 0 45 1 0
#> 83.2 24.00 0 6 0 0
#> 46 24.00 0 71 0 0
#> 152 24.00 0 36 0 1
#> 35 24.00 0 51 0 0
#> 84 24.00 0 39 0 1
#> 62 24.00 0 71 0 0
#> 64.2 24.00 0 43 0 0
#> 84.1 24.00 0 39 0 1
#> 31.1 24.00 0 36 0 1
#> 141 24.00 0 44 1 0
#> 198 24.00 0 66 0 1
#> 102 24.00 0 49 0 0
#> 75.1 24.00 0 21 1 0
#> 112.1 24.00 0 61 0 0
#> 172.2 24.00 0 41 0 0
#> 152.1 24.00 0 36 0 1
#> 104 24.00 0 50 1 0
#> 109 24.00 0 48 0 0
#> 84.2 24.00 0 39 0 1
#> 142.1 24.00 0 53 0 0
#> 115 24.00 0 NA 1 0
#> 146 24.00 0 63 1 0
#> 173 24.00 0 19 0 1
#> 21 24.00 0 47 0 0
#> 82.1 24.00 0 34 0 0
#> 73 24.00 0 NA 0 1
#> 48 24.00 0 31 1 0
#> 163.2 24.00 0 66 0 0
#> 147 24.00 0 76 1 0
#> 62.1 24.00 0 71 0 0
#> 62.2 24.00 0 71 0 0
#> 116 24.00 0 58 0 1
#> 53 24.00 0 32 0 1
#> 165.1 24.00 0 47 0 0
#> 7.1 24.00 0 37 1 0
#> 74 24.00 0 43 0 1
#> 147.1 24.00 0 76 1 0
#> 75.2 24.00 0 21 1 0
#> 142.2 24.00 0 53 0 0
#> 198.1 24.00 0 66 0 1
#> 104.1 24.00 0 50 1 0
#> 151.1 24.00 0 42 0 0
#> 162 24.00 0 51 0 0
#> 95 24.00 0 68 0 1
#> 38.2 24.00 0 31 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.10 NA NA NA
#> 2 age, Cure model 0.0174 NA NA NA
#> 3 grade_ii, Cure model 0.445 NA NA NA
#> 4 grade_iii, Cure model 1.01 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0105 NA NA NA
#> 2 grade_ii, Survival model 0.857 NA NA NA
#> 3 grade_iii, Survival model 0.111 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.09610 0.01741 0.44486 1.00552
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 261.7
#> Residual Deviance: 251.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.09609759 0.01741399 0.44485621 1.00551626
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01045353 0.85713482 0.11069606
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.0036128471 0.8012671743 0.4116265658 0.4665546308 0.5872078870
#> [6] 0.3795569782 0.4440831650 0.0767046368 0.4886316193 0.9374235451
#> [11] 0.5110578365 0.9791576894 0.1068284036 0.5547546159 0.3690449608
#> [16] 0.8849864939 0.2657189142 0.4116265658 0.0104059165 0.6291216780
#> [21] 0.0036128471 0.9791576894 0.7148099338 0.8540087564 0.1233939332
#> [26] 0.9479077886 0.4116265658 0.0209777384 0.4552770064 0.0626140852
#> [31] 0.3161974901 0.8434233106 0.7039195389 0.9687728830 0.9164972768
#> [36] 0.1233939332 0.4886316193 0.0282561018 0.7582156093 0.6503266425
#> [41] 0.1577532717 0.0418059384 0.0626140852 0.8954788151 0.3369474890
#> [46] 0.3058245623 0.1917465653 0.1488214189 0.7798220951 0.4665546308
#> [51] 0.6609451050 0.3901619865 0.2096301323 0.7257501881 0.8540087564
#> [56] 0.0008161083 0.0843906361 0.2465929591 0.8012671743 0.5110578365
#> [61] 0.1577532717 0.5110578365 0.1745124407 0.6930798131 0.5436060614
#> [66] 0.6291216780 0.2856220392 0.3161974901 0.2370891186 0.0418059384
#> [71] 0.1233939332 0.7582156093 0.2755925304 0.5872078870 0.0349373863
#> [76] 0.6822753820 0.7367298344 0.0557727383 0.1745124407 0.3369474890
#> [81] 0.8540087564 0.5547546159 0.2007056749 0.5872078870 0.2096301323
#> [86] 0.2465929591 0.8222014291 0.3901619865 0.0843906361 0.7367298344
#> [91] 0.0104059165 0.8327808734 0.9583150374 0.7798220951 0.6609451050
#> [96] 0.2856220392 0.0843906361 0.1068284036 0.3583990328 0.5872078870
#> [101] 0.2276935482 0.9269939170 0.5547546159 0.9059998949 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#>
#> $Time
#> 86 154 171 85 167 111 130 169 5 16 79 127 66
#> 23.81 12.63 16.57 16.44 15.55 17.45 16.47 22.41 16.43 8.71 16.23 3.53 22.13
#> 125 134 52 76 171.1 168 29 86.1 127.1 81 107 136 149
#> 15.65 17.81 10.42 19.22 16.57 23.72 15.45 23.81 3.53 14.06 11.18 21.83 8.37
#> 171.2 164 181 15 108 49 57 25 101 136.1 5.1 129 14
#> 16.57 23.60 16.46 22.68 18.29 12.19 14.46 6.32 9.97 21.83 16.43 23.41 12.89
#> 18 153 92 15.1 61 51 8 90 197 140 192 157 23
#> 15.21 21.33 22.92 22.68 10.12 18.23 18.43 20.94 21.60 12.68 16.44 15.10 16.92
#> 166 155 107.1 24 194 58 154.1 79.1 153.1 79.2 99 96 26
#> 19.98 13.08 11.18 23.89 22.40 19.34 12.63 16.23 21.33 16.23 21.19 14.54 15.77
#> 29.1 179 108.1 170 92.1 136.2 14.1 97 167.1 69 180 123 63
#> 15.45 18.63 18.29 19.54 22.92 21.83 12.89 19.14 15.55 23.23 14.82 13.00 22.77
#> 36 51.1 107.2 125.1 158 167.2 166.1 58.1 42 23.1 194.1 123.1 168.1
#> 21.19 18.23 11.18 15.65 20.14 15.55 19.98 19.34 12.43 16.92 22.40 13.00 23.72
#> 56 77 140.1 157.1 179.1 194.2 66.1 40 167.3 105 187 125.2 145
#> 12.21 7.27 12.68 15.10 18.63 22.40 22.13 18.00 15.55 19.75 9.92 15.65 10.07
#> 83 22 64 182 20 112 163 172 103 87 151 54 193
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165 3 142 38 156 172.1 94 9 20.1 72 54.1 163.1 38.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75 144 3.1 64.1 132 28 83.1 28.1 65 31 182.1 1 7
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94.1 17 82 137 83.2 46 152 35 84 62 64.2 84.1 31.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 141 198 102 75.1 112.1 172.2 152.1 104 109 84.2 142.1 146 173
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 21 82.1 48 163.2 147 62.1 62.2 116 53 165.1 7.1 74 147.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75.2 142.2 198.1 104.1 151.1 162 95 38.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[18]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01457699 0.44917991 0.31675248
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.507791619 0.005049525 0.464790062
#> grade_iii, Cure model
#> 0.851085257
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 30 17.43 1 78 0 0
#> 125 15.65 1 67 1 0
#> 114 13.68 1 NA 0 0
#> 139 21.49 1 63 1 0
#> 184 17.77 1 38 0 0
#> 140 12.68 1 59 1 0
#> 42 12.43 1 49 0 1
#> 164 23.60 1 76 0 1
#> 86 23.81 1 58 0 1
#> 110 17.56 1 65 0 1
#> 60 13.15 1 38 1 0
#> 150 20.33 1 48 0 0
#> 158 20.14 1 74 1 0
#> 26 15.77 1 49 0 1
#> 60.1 13.15 1 38 1 0
#> 36 21.19 1 48 0 1
#> 153 21.33 1 55 1 0
#> 129 23.41 1 53 1 0
#> 90 20.94 1 50 0 1
#> 50 10.02 1 NA 1 0
#> 179 18.63 1 42 0 0
#> 105 19.75 1 60 0 0
#> 68 20.62 1 44 0 0
#> 86.1 23.81 1 58 0 1
#> 124 9.73 1 NA 1 0
#> 13 14.34 1 54 0 1
#> 77 7.27 1 67 0 1
#> 153.1 21.33 1 55 1 0
#> 16 8.71 1 71 0 1
#> 97 19.14 1 65 0 1
#> 91 5.33 1 61 0 1
#> 108 18.29 1 39 0 1
#> 32 20.90 1 37 1 0
#> 166 19.98 1 48 0 0
#> 40 18.00 1 28 1 0
#> 10 10.53 1 34 0 0
#> 81 14.06 1 34 0 0
#> 5 16.43 1 51 0 1
#> 108.1 18.29 1 39 0 1
#> 24 23.89 1 38 0 0
#> 190 20.81 1 42 1 0
#> 150.1 20.33 1 48 0 0
#> 88 18.37 1 47 0 0
#> 175 21.91 1 43 0 0
#> 42.1 12.43 1 49 0 1
#> 188 16.16 1 46 0 1
#> 41 18.02 1 40 1 0
#> 49 12.19 1 48 1 0
#> 181 16.46 1 45 0 1
#> 43 12.10 1 61 0 1
#> 16.1 8.71 1 71 0 1
#> 134 17.81 1 47 1 0
#> 117 17.46 1 26 0 1
#> 192 16.44 1 31 1 0
#> 106 16.67 1 49 1 0
#> 18 15.21 1 49 1 0
#> 158.1 20.14 1 74 1 0
#> 18.1 15.21 1 49 1 0
#> 26.1 15.77 1 49 0 1
#> 164.1 23.60 1 76 0 1
#> 57 14.46 1 45 0 1
#> 107 11.18 1 54 1 0
#> 139.1 21.49 1 63 1 0
#> 129.1 23.41 1 53 1 0
#> 85 16.44 1 36 0 0
#> 60.2 13.15 1 38 1 0
#> 134.1 17.81 1 47 1 0
#> 140.1 12.68 1 59 1 0
#> 41.1 18.02 1 40 1 0
#> 136 21.83 1 43 0 1
#> 145 10.07 1 65 1 0
#> 51 18.23 1 83 0 1
#> 184.1 17.77 1 38 0 0
#> 192.1 16.44 1 31 1 0
#> 41.2 18.02 1 40 1 0
#> 70 7.38 1 30 1 0
#> 169 22.41 1 46 0 0
#> 101 9.97 1 10 0 1
#> 157 15.10 1 47 0 0
#> 105.1 19.75 1 60 0 0
#> 57.1 14.46 1 45 0 1
#> 108.2 18.29 1 39 0 1
#> 25 6.32 1 34 1 0
#> 167 15.55 1 56 1 0
#> 184.2 17.77 1 38 0 0
#> 199 19.81 1 NA 0 1
#> 56 12.21 1 60 0 0
#> 177 12.53 1 75 0 0
#> 114.1 13.68 1 NA 0 0
#> 167.1 15.55 1 56 1 0
#> 77.1 7.27 1 67 0 1
#> 97.1 19.14 1 65 0 1
#> 76 19.22 1 54 0 1
#> 41.3 18.02 1 40 1 0
#> 166.1 19.98 1 48 0 0
#> 145.1 10.07 1 65 1 0
#> 66 22.13 1 53 0 0
#> 5.1 16.43 1 51 0 1
#> 195 11.76 1 NA 1 0
#> 86.2 23.81 1 58 0 1
#> 181.1 16.46 1 45 0 1
#> 5.2 16.43 1 51 0 1
#> 171 16.57 1 41 0 1
#> 97.2 19.14 1 65 0 1
#> 60.3 13.15 1 38 1 0
#> 60.4 13.15 1 38 1 0
#> 59 10.16 1 NA 1 0
#> 5.3 16.43 1 51 0 1
#> 76.1 19.22 1 54 0 1
#> 99 21.19 1 38 0 1
#> 68.1 20.62 1 44 0 0
#> 190.1 20.81 1 42 1 0
#> 112 24.00 0 61 0 0
#> 122 24.00 0 66 0 0
#> 71 24.00 0 51 0 0
#> 116 24.00 0 58 0 1
#> 132 24.00 0 55 0 0
#> 71.1 24.00 0 51 0 0
#> 82 24.00 0 34 0 0
#> 94 24.00 0 51 0 1
#> 31 24.00 0 36 0 1
#> 27 24.00 0 63 1 0
#> 115 24.00 0 NA 1 0
#> 38 24.00 0 31 1 0
#> 160 24.00 0 31 1 0
#> 95 24.00 0 68 0 1
#> 160.1 24.00 0 31 1 0
#> 200 24.00 0 64 0 0
#> 173 24.00 0 19 0 1
#> 147 24.00 0 76 1 0
#> 83 24.00 0 6 0 0
#> 118 24.00 0 44 1 0
#> 137 24.00 0 45 1 0
#> 162 24.00 0 51 0 0
#> 94.1 24.00 0 51 0 1
#> 28 24.00 0 67 1 0
#> 138 24.00 0 44 1 0
#> 98 24.00 0 34 1 0
#> 148 24.00 0 61 1 0
#> 103 24.00 0 56 1 0
#> 156 24.00 0 50 1 0
#> 19 24.00 0 57 0 1
#> 44 24.00 0 56 0 0
#> 115.1 24.00 0 NA 1 0
#> 174 24.00 0 49 1 0
#> 7 24.00 0 37 1 0
#> 178 24.00 0 52 1 0
#> 102 24.00 0 49 0 0
#> 191 24.00 0 60 0 1
#> 131 24.00 0 66 0 0
#> 20 24.00 0 46 1 0
#> 95.1 24.00 0 68 0 1
#> 138.1 24.00 0 44 1 0
#> 163 24.00 0 66 0 0
#> 144 24.00 0 28 0 1
#> 172 24.00 0 41 0 0
#> 131.1 24.00 0 66 0 0
#> 138.2 24.00 0 44 1 0
#> 84 24.00 0 39 0 1
#> 151 24.00 0 42 0 0
#> 48 24.00 0 31 1 0
#> 98.1 24.00 0 34 1 0
#> 176 24.00 0 43 0 1
#> 165 24.00 0 47 0 0
#> 80 24.00 0 41 0 0
#> 137.1 24.00 0 45 1 0
#> 112.1 24.00 0 61 0 0
#> 54 24.00 0 53 1 0
#> 116.1 24.00 0 58 0 1
#> 178.1 24.00 0 52 1 0
#> 33 24.00 0 53 0 0
#> 3 24.00 0 31 1 0
#> 103.1 24.00 0 56 1 0
#> 27.1 24.00 0 63 1 0
#> 148.1 24.00 0 61 1 0
#> 46 24.00 0 71 0 0
#> 122.1 24.00 0 66 0 0
#> 44.1 24.00 0 56 0 0
#> 144.1 24.00 0 28 0 1
#> 163.1 24.00 0 66 0 0
#> 102.1 24.00 0 49 0 0
#> 138.3 24.00 0 44 1 0
#> 87 24.00 0 27 0 0
#> 38.1 24.00 0 31 1 0
#> 173.1 24.00 0 19 0 1
#> 38.2 24.00 0 31 1 0
#> 62 24.00 0 71 0 0
#> 151.1 24.00 0 42 0 0
#> 28.1 24.00 0 67 1 0
#> 47 24.00 0 38 0 1
#> 120 24.00 0 68 0 1
#> 67 24.00 0 25 0 0
#> 120.1 24.00 0 68 0 1
#> 95.2 24.00 0 68 0 1
#> 151.2 24.00 0 42 0 0
#> 191.1 24.00 0 60 0 1
#> 173.2 24.00 0 19 0 1
#> 94.2 24.00 0 51 0 1
#> 35 24.00 0 51 0 0
#> 191.2 24.00 0 60 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.508 NA NA NA
#> 2 age, Cure model 0.00505 NA NA NA
#> 3 grade_ii, Cure model 0.465 NA NA NA
#> 4 grade_iii, Cure model 0.851 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0146 NA NA NA
#> 2 grade_ii, Survival model 0.449 NA NA NA
#> 3 grade_iii, Survival model 0.317 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.50779 0.00505 0.46479 0.85109
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 262.9
#> Residual Deviance: 257.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.507791619 0.005049525 0.464790062 0.851085257
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01457699 0.44917991 0.31675248
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.3790493750 0.5462443537 0.0354281914 0.3274229882 0.7296614020
#> [6] 0.7681548037 0.0063758905 0.0017717944 0.3578519679 0.6682966284
#> [11] 0.1029973297 0.1163672032 0.5228747501 0.6682966284 0.0557118806
#> [16] 0.0452292063 0.0117989270 0.0667489373 0.2036712355 0.1454408250
#> [21] 0.0904483212 0.0017717944 0.6431317517 0.9437075740 0.0452292063
#> [26] 0.9022109509 0.1778467091 0.9858047129 0.2222439986 0.0726902667
#> [31] 0.1304964398 0.2976696928 0.8477138798 0.6556670064 0.4665075757
#> [36] 0.2222439986 0.0003109641 0.0786740173 0.1029973297 0.2128571442
#> [41] 0.0261067347 0.7681548037 0.5112291470 0.2598201496 0.8074987424
#> [46] 0.4117032880 0.8208197996 0.9022109509 0.3076060915 0.3684414614
#> [51] 0.4336568935 0.3898628418 0.5820546826 0.1163672032 0.5820546826
#> [56] 0.5228747501 0.0063758905 0.6184840748 0.8342357571 0.0354281914
#> [61] 0.0117989270 0.4336568935 0.6682966284 0.3076060915 0.7296614020
#> [66] 0.2598201496 0.0306725984 0.8612762761 0.2499849574 0.3274229882
#> [71] 0.4336568935 0.2598201496 0.9298077298 0.0180623007 0.8885216417
#> [76] 0.6061775242 0.1454408250 0.6184840748 0.2222439986 0.9716979642
#> [81] 0.5581625303 0.3274229882 0.7942262090 0.7551526157 0.5581625303
#> [86] 0.9437075740 0.1778467091 0.1613381370 0.2598201496 0.1304964398
#> [91] 0.8612762761 0.0218856083 0.4665075757 0.0017717944 0.4117032880
#> [96] 0.4665075757 0.4007466207 0.1778467091 0.6682966284 0.6682966284
#> [101] 0.4665075757 0.1613381370 0.0557118806 0.0904483212 0.0786740173
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [191] 0.0000000000
#>
#> $Time
#> 30 125 139 184 140 42 164 86 110 60 150 158 26
#> 17.43 15.65 21.49 17.77 12.68 12.43 23.60 23.81 17.56 13.15 20.33 20.14 15.77
#> 60.1 36 153 129 90 179 105 68 86.1 13 77 153.1 16
#> 13.15 21.19 21.33 23.41 20.94 18.63 19.75 20.62 23.81 14.34 7.27 21.33 8.71
#> 97 91 108 32 166 40 10 81 5 108.1 24 190 150.1
#> 19.14 5.33 18.29 20.90 19.98 18.00 10.53 14.06 16.43 18.29 23.89 20.81 20.33
#> 88 175 42.1 188 41 49 181 43 16.1 134 117 192 106
#> 18.37 21.91 12.43 16.16 18.02 12.19 16.46 12.10 8.71 17.81 17.46 16.44 16.67
#> 18 158.1 18.1 26.1 164.1 57 107 139.1 129.1 85 60.2 134.1 140.1
#> 15.21 20.14 15.21 15.77 23.60 14.46 11.18 21.49 23.41 16.44 13.15 17.81 12.68
#> 41.1 136 145 51 184.1 192.1 41.2 70 169 101 157 105.1 57.1
#> 18.02 21.83 10.07 18.23 17.77 16.44 18.02 7.38 22.41 9.97 15.10 19.75 14.46
#> 108.2 25 167 184.2 56 177 167.1 77.1 97.1 76 41.3 166.1 145.1
#> 18.29 6.32 15.55 17.77 12.21 12.53 15.55 7.27 19.14 19.22 18.02 19.98 10.07
#> 66 5.1 86.2 181.1 5.2 171 97.2 60.3 60.4 5.3 76.1 99 68.1
#> 22.13 16.43 23.81 16.46 16.43 16.57 19.14 13.15 13.15 16.43 19.22 21.19 20.62
#> 190.1 112 122 71 116 132 71.1 82 94 31 27 38 160
#> 20.81 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95 160.1 200 173 147 83 118 137 162 94.1 28 138 98
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148 103 156 19 44 174 7 178 102 191 131 20 95.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 138.1 163 144 172 131.1 138.2 84 151 48 98.1 176 165 80
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137.1 112.1 54 116.1 178.1 33 3 103.1 27.1 148.1 46 122.1 44.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 144.1 163.1 102.1 138.3 87 38.1 173.1 38.2 62 151.1 28.1 47 120
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67 120.1 95.2 151.2 191.1 173.2 94.2 35 191.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[19]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.0004026051 0.2652998320 0.1835936430
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.485819878 0.008288109 -0.032669018
#> grade_iii, Cure model
#> 0.898928101
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 195 11.76 1 NA 1 0
#> 153 21.33 1 55 1 0
#> 192 16.44 1 31 1 0
#> 88 18.37 1 47 0 0
#> 60 13.15 1 38 1 0
#> 159 10.55 1 50 0 1
#> 10 10.53 1 34 0 0
#> 114 13.68 1 NA 0 0
#> 18 15.21 1 49 1 0
#> 184 17.77 1 38 0 0
#> 88.1 18.37 1 47 0 0
#> 56 12.21 1 60 0 0
#> 99 21.19 1 38 0 1
#> 45 17.42 1 54 0 1
#> 140 12.68 1 59 1 0
#> 167 15.55 1 56 1 0
#> 68 20.62 1 44 0 0
#> 197 21.60 1 69 1 0
#> 25 6.32 1 34 1 0
#> 125 15.65 1 67 1 0
#> 51 18.23 1 83 0 1
#> 59 10.16 1 NA 1 0
#> 184.1 17.77 1 38 0 0
#> 92 22.92 1 47 0 1
#> 166 19.98 1 48 0 0
#> 107 11.18 1 54 1 0
#> 16 8.71 1 71 0 1
#> 125.1 15.65 1 67 1 0
#> 88.2 18.37 1 47 0 0
#> 13 14.34 1 54 0 1
#> 55 19.34 1 69 0 1
#> 125.2 15.65 1 67 1 0
#> 110 17.56 1 65 0 1
#> 90 20.94 1 50 0 1
#> 10.1 10.53 1 34 0 0
#> 114.1 13.68 1 NA 0 0
#> 100 16.07 1 60 0 0
#> 190 20.81 1 42 1 0
#> 159.1 10.55 1 50 0 1
#> 30 17.43 1 78 0 0
#> 99.1 21.19 1 38 0 1
#> 183 9.24 1 67 1 0
#> 56.1 12.21 1 60 0 0
#> 96 14.54 1 33 0 1
#> 66 22.13 1 53 0 0
#> 177 12.53 1 75 0 0
#> 149 8.37 1 33 1 0
#> 117 17.46 1 26 0 1
#> 145 10.07 1 65 1 0
#> 4 17.64 1 NA 0 1
#> 88.3 18.37 1 47 0 0
#> 51.1 18.23 1 83 0 1
#> 77 7.27 1 67 0 1
#> 90.1 20.94 1 50 0 1
#> 86 23.81 1 58 0 1
#> 168 23.72 1 70 0 0
#> 127 3.53 1 62 0 1
#> 55.1 19.34 1 69 0 1
#> 167.1 15.55 1 56 1 0
#> 10.2 10.53 1 34 0 0
#> 139 21.49 1 63 1 0
#> 8 18.43 1 32 0 0
#> 179 18.63 1 42 0 0
#> 43 12.10 1 61 0 1
#> 57 14.46 1 45 0 1
#> 45.1 17.42 1 54 0 1
#> 136 21.83 1 43 0 1
#> 26 15.77 1 49 0 1
#> 26.1 15.77 1 49 0 1
#> 68.1 20.62 1 44 0 0
#> 155 13.08 1 26 0 0
#> 159.2 10.55 1 50 0 1
#> 184.2 17.77 1 38 0 0
#> 4.1 17.64 1 NA 0 1
#> 190.1 20.81 1 42 1 0
#> 5 16.43 1 51 0 1
#> 14 12.89 1 21 0 0
#> 15 22.68 1 48 0 0
#> 4.2 17.64 1 NA 0 1
#> 30.1 17.43 1 78 0 0
#> 111 17.45 1 47 0 1
#> 110.1 17.56 1 65 0 1
#> 30.2 17.43 1 78 0 0
#> 68.2 20.62 1 44 0 0
#> 93 10.33 1 52 0 1
#> 36 21.19 1 48 0 1
#> 153.1 21.33 1 55 1 0
#> 58 19.34 1 39 0 0
#> 130 16.47 1 53 0 1
#> 49 12.19 1 48 1 0
#> 197.1 21.60 1 69 1 0
#> 171 16.57 1 41 0 1
#> 114.2 13.68 1 NA 0 0
#> 167.2 15.55 1 56 1 0
#> 99.2 21.19 1 38 0 1
#> 92.1 22.92 1 47 0 1
#> 91 5.33 1 61 0 1
#> 177.1 12.53 1 75 0 0
#> 139.1 21.49 1 63 1 0
#> 140.1 12.68 1 59 1 0
#> 14.1 12.89 1 21 0 0
#> 66.1 22.13 1 53 0 0
#> 13.1 14.34 1 54 0 1
#> 91.1 5.33 1 61 0 1
#> 117.1 17.46 1 26 0 1
#> 139.2 21.49 1 63 1 0
#> 91.2 5.33 1 61 0 1
#> 190.2 20.81 1 42 1 0
#> 187 9.92 1 39 1 0
#> 40 18.00 1 28 1 0
#> 24 23.89 1 38 0 0
#> 99.3 21.19 1 38 0 1
#> 131 24.00 0 66 0 0
#> 156 24.00 0 50 1 0
#> 17 24.00 0 38 0 1
#> 161 24.00 0 45 0 0
#> 156.1 24.00 0 50 1 0
#> 71 24.00 0 51 0 0
#> 22 24.00 0 52 1 0
#> 71.1 24.00 0 51 0 0
#> 62 24.00 0 71 0 0
#> 104 24.00 0 50 1 0
#> 146 24.00 0 63 1 0
#> 22.1 24.00 0 52 1 0
#> 35 24.00 0 51 0 0
#> 1 24.00 0 23 1 0
#> 17.1 24.00 0 38 0 1
#> 47 24.00 0 38 0 1
#> 141 24.00 0 44 1 0
#> 132 24.00 0 55 0 0
#> 103 24.00 0 56 1 0
#> 75 24.00 0 21 1 0
#> 142 24.00 0 53 0 0
#> 174 24.00 0 49 1 0
#> 1.1 24.00 0 23 1 0
#> 118 24.00 0 44 1 0
#> 73 24.00 0 NA 0 1
#> 148 24.00 0 61 1 0
#> 80 24.00 0 41 0 0
#> 103.1 24.00 0 56 1 0
#> 131.1 24.00 0 66 0 0
#> 73.1 24.00 0 NA 0 1
#> 161.1 24.00 0 45 0 0
#> 200 24.00 0 64 0 0
#> 71.2 24.00 0 51 0 0
#> 19 24.00 0 57 0 1
#> 1.2 24.00 0 23 1 0
#> 165 24.00 0 47 0 0
#> 95 24.00 0 68 0 1
#> 94 24.00 0 51 0 1
#> 2 24.00 0 9 0 0
#> 22.2 24.00 0 52 1 0
#> 122 24.00 0 66 0 0
#> 182 24.00 0 35 0 0
#> 138 24.00 0 44 1 0
#> 121 24.00 0 57 1 0
#> 116 24.00 0 58 0 1
#> 47.1 24.00 0 38 0 1
#> 34 24.00 0 36 0 0
#> 165.1 24.00 0 47 0 0
#> 191 24.00 0 60 0 1
#> 95.1 24.00 0 68 0 1
#> 143 24.00 0 51 0 0
#> 28 24.00 0 67 1 0
#> 142.1 24.00 0 53 0 0
#> 20 24.00 0 46 1 0
#> 147 24.00 0 76 1 0
#> 143.1 24.00 0 51 0 0
#> 174.1 24.00 0 49 1 0
#> 87 24.00 0 27 0 0
#> 126 24.00 0 48 0 0
#> 120 24.00 0 68 0 1
#> 122.1 24.00 0 66 0 0
#> 147.1 24.00 0 76 1 0
#> 172 24.00 0 41 0 0
#> 64 24.00 0 43 0 0
#> 102 24.00 0 49 0 0
#> 121.1 24.00 0 57 1 0
#> 178 24.00 0 52 1 0
#> 11 24.00 0 42 0 1
#> 198 24.00 0 66 0 1
#> 35.1 24.00 0 51 0 0
#> 83 24.00 0 6 0 0
#> 31 24.00 0 36 0 1
#> 141.1 24.00 0 44 1 0
#> 102.1 24.00 0 49 0 0
#> 200.1 24.00 0 64 0 0
#> 120.1 24.00 0 68 0 1
#> 160 24.00 0 31 1 0
#> 112 24.00 0 61 0 0
#> 156.2 24.00 0 50 1 0
#> 22.3 24.00 0 52 1 0
#> 17.2 24.00 0 38 0 1
#> 67 24.00 0 25 0 0
#> 132.1 24.00 0 55 0 0
#> 34.1 24.00 0 36 0 0
#> 160.1 24.00 0 31 1 0
#> 116.1 24.00 0 58 0 1
#> 116.2 24.00 0 58 0 1
#> 178.1 24.00 0 52 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.486 NA NA NA
#> 2 age, Cure model 0.00829 NA NA NA
#> 3 grade_ii, Cure model -0.0327 NA NA NA
#> 4 grade_iii, Cure model 0.899 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.000403 NA NA NA
#> 2 grade_ii, Survival model 0.265 NA NA NA
#> 3 grade_iii, Survival model 0.184 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.485820 0.008288 -0.032669 0.898928
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 261.7
#> Residual Deviance: 252.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.485819878 0.008288109 -0.032669018 0.898928101
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.0004026051 0.2652998320 0.1835936430
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.186450331 0.592556762 0.388386959 0.734922542 0.847642175 0.873138706
#> [7] 0.690986178 0.453908093 0.388386959 0.804377707 0.207726573 0.555741782
#> [13] 0.769799695 0.664675377 0.302970864 0.131038320 0.958208396 0.638075452
#> [19] 0.425555780 0.453908093 0.055431720 0.331293841 0.839010106 0.932791807
#> [25] 0.638075452 0.388386959 0.717481901 0.341022918 0.638075452 0.481784146
#> [31] 0.254925271 0.873138706 0.610866736 0.274696192 0.847642175 0.528253539
#> [37] 0.207726573 0.924287773 0.804377707 0.699838499 0.093139171 0.787083046
#> [43] 0.941282862 0.500428443 0.907214929 0.388386959 0.425555780 0.949752022
#> [49] 0.254925271 0.025342601 0.040275658 0.991616861 0.341022918 0.664675377
#> [55] 0.873138706 0.154496639 0.378760000 0.369136185 0.830353476 0.708670080
#> [61] 0.555741782 0.118086091 0.620012659 0.620012659 0.302970864 0.743665581
#> [67] 0.847642175 0.453908093 0.274696192 0.601724082 0.752409692 0.079800363
#> [73] 0.528253539 0.518942458 0.481784146 0.528253539 0.302970864 0.898645416
#> [79] 0.207726573 0.186450331 0.341022918 0.583348467 0.821681262 0.131038320
#> [85] 0.574114498 0.664675377 0.207726573 0.055431720 0.966643474 0.787083046
#> [91] 0.154496639 0.769799695 0.752409692 0.093139171 0.717481901 0.966643474
#> [97] 0.500428443 0.154496639 0.966643474 0.274696192 0.915762630 0.444428302
#> [103] 0.009180395 0.207726573 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 153 192 88 60 159 10 18 184 88.1 56 99 45 140
#> 21.33 16.44 18.37 13.15 10.55 10.53 15.21 17.77 18.37 12.21 21.19 17.42 12.68
#> 167 68 197 25 125 51 184.1 92 166 107 16 125.1 88.2
#> 15.55 20.62 21.60 6.32 15.65 18.23 17.77 22.92 19.98 11.18 8.71 15.65 18.37
#> 13 55 125.2 110 90 10.1 100 190 159.1 30 99.1 183 56.1
#> 14.34 19.34 15.65 17.56 20.94 10.53 16.07 20.81 10.55 17.43 21.19 9.24 12.21
#> 96 66 177 149 117 145 88.3 51.1 77 90.1 86 168 127
#> 14.54 22.13 12.53 8.37 17.46 10.07 18.37 18.23 7.27 20.94 23.81 23.72 3.53
#> 55.1 167.1 10.2 139 8 179 43 57 45.1 136 26 26.1 68.1
#> 19.34 15.55 10.53 21.49 18.43 18.63 12.10 14.46 17.42 21.83 15.77 15.77 20.62
#> 155 159.2 184.2 190.1 5 14 15 30.1 111 110.1 30.2 68.2 93
#> 13.08 10.55 17.77 20.81 16.43 12.89 22.68 17.43 17.45 17.56 17.43 20.62 10.33
#> 36 153.1 58 130 49 197.1 171 167.2 99.2 92.1 91 177.1 139.1
#> 21.19 21.33 19.34 16.47 12.19 21.60 16.57 15.55 21.19 22.92 5.33 12.53 21.49
#> 140.1 14.1 66.1 13.1 91.1 117.1 139.2 91.2 190.2 187 40 24 99.3
#> 12.68 12.89 22.13 14.34 5.33 17.46 21.49 5.33 20.81 9.92 18.00 23.89 21.19
#> 131 156 17 161 156.1 71 22 71.1 62 104 146 22.1 35
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1 17.1 47 141 132 103 75 142 174 1.1 118 148 80
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103.1 131.1 161.1 200 71.2 19 1.2 165 95 94 2 22.2 122
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 182 138 121 116 47.1 34 165.1 191 95.1 143 28 142.1 20
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 147 143.1 174.1 87 126 120 122.1 147.1 172 64 102 121.1 178
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 11 198 35.1 83 31 141.1 102.1 200.1 120.1 160 112 156.2 22.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 17.2 67 132.1 34.1 160.1 116.1 116.2 178.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[20]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01079619 0.31977637 0.43803346
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.47464945 -0.01068671 -0.14455562
#> grade_iii, Cure model
#> 1.16124680
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 130 16.47 1 53 0 1
#> 37 12.52 1 57 1 0
#> 52 10.42 1 52 0 1
#> 70 7.38 1 30 1 0
#> 150 20.33 1 48 0 0
#> 168 23.72 1 70 0 0
#> 130.1 16.47 1 53 0 1
#> 78 23.88 1 43 0 0
#> 140 12.68 1 59 1 0
#> 180 14.82 1 37 0 0
#> 140.1 12.68 1 59 1 0
#> 114 13.68 1 NA 0 0
#> 164 23.60 1 76 0 1
#> 107 11.18 1 54 1 0
#> 175 21.91 1 43 0 0
#> 153 21.33 1 55 1 0
#> 69 23.23 1 25 0 1
#> 23 16.92 1 61 0 0
#> 184 17.77 1 38 0 0
#> 50 10.02 1 NA 1 0
#> 96 14.54 1 33 0 1
#> 97 19.14 1 65 0 1
#> 166 19.98 1 48 0 0
#> 155 13.08 1 26 0 0
#> 45 17.42 1 54 0 1
#> 16 8.71 1 71 0 1
#> 134 17.81 1 47 1 0
#> 43 12.10 1 61 0 1
#> 155.1 13.08 1 26 0 0
#> 85 16.44 1 36 0 0
#> 32 20.90 1 37 1 0
#> 5 16.43 1 51 0 1
#> 154 12.63 1 20 1 0
#> 110 17.56 1 65 0 1
#> 128 20.35 1 35 0 1
#> 15 22.68 1 48 0 0
#> 26 15.77 1 49 0 1
#> 150.1 20.33 1 48 0 0
#> 170 19.54 1 43 0 1
#> 96.1 14.54 1 33 0 1
#> 70.1 7.38 1 30 1 0
#> 63 22.77 1 31 1 0
#> 106 16.67 1 49 1 0
#> 197 21.60 1 69 1 0
#> 56 12.21 1 60 0 0
#> 59 10.16 1 NA 1 0
#> 125 15.65 1 67 1 0
#> 106.1 16.67 1 49 1 0
#> 14 12.89 1 21 0 0
#> 30 17.43 1 78 0 0
#> 10 10.53 1 34 0 0
#> 190 20.81 1 42 1 0
#> 26.1 15.77 1 49 0 1
#> 91 5.33 1 61 0 1
#> 155.2 13.08 1 26 0 0
#> 134.1 17.81 1 47 1 0
#> 10.1 10.53 1 34 0 0
#> 179 18.63 1 42 0 0
#> 180.1 14.82 1 37 0 0
#> 15.1 22.68 1 48 0 0
#> 29 15.45 1 68 1 0
#> 79 16.23 1 54 1 0
#> 189 10.51 1 NA 1 0
#> 23.1 16.92 1 61 0 0
#> 85.1 16.44 1 36 0 0
#> 43.1 12.10 1 61 0 1
#> 157 15.10 1 47 0 0
#> 26.2 15.77 1 49 0 1
#> 180.2 14.82 1 37 0 0
#> 111 17.45 1 47 0 1
#> 96.2 14.54 1 33 0 1
#> 88 18.37 1 47 0 0
#> 78.1 23.88 1 43 0 0
#> 187 9.92 1 39 1 0
#> 128.1 20.35 1 35 0 1
#> 100 16.07 1 60 0 0
#> 124 9.73 1 NA 1 0
#> 166.1 19.98 1 48 0 0
#> 6 15.64 1 39 0 0
#> 180.3 14.82 1 37 0 0
#> 153.1 21.33 1 55 1 0
#> 41 18.02 1 40 1 0
#> 130.2 16.47 1 53 0 1
#> 106.2 16.67 1 49 1 0
#> 58 19.34 1 39 0 0
#> 4 17.64 1 NA 0 1
#> 85.2 16.44 1 36 0 0
#> 171 16.57 1 41 0 1
#> 101 9.97 1 10 0 1
#> 30.1 17.43 1 78 0 0
#> 168.1 23.72 1 70 0 0
#> 195 11.76 1 NA 1 0
#> 78.2 23.88 1 43 0 0
#> 195.1 11.76 1 NA 1 0
#> 32.1 20.90 1 37 1 0
#> 134.2 17.81 1 47 1 0
#> 14.1 12.89 1 21 0 0
#> 194 22.40 1 38 0 1
#> 77 7.27 1 67 0 1
#> 117 17.46 1 26 0 1
#> 101.1 9.97 1 10 0 1
#> 105 19.75 1 60 0 0
#> 129 23.41 1 53 1 0
#> 43.2 12.10 1 61 0 1
#> 18 15.21 1 49 1 0
#> 70.2 7.38 1 30 1 0
#> 153.2 21.33 1 55 1 0
#> 15.2 22.68 1 48 0 0
#> 194.1 22.40 1 38 0 1
#> 76 19.22 1 54 0 1
#> 88.1 18.37 1 47 0 0
#> 171.1 16.57 1 41 0 1
#> 186 24.00 0 45 1 0
#> 174 24.00 0 49 1 0
#> 28 24.00 0 67 1 0
#> 67 24.00 0 25 0 0
#> 200 24.00 0 64 0 0
#> 120 24.00 0 68 0 1
#> 151 24.00 0 42 0 0
#> 141 24.00 0 44 1 0
#> 112 24.00 0 61 0 0
#> 162 24.00 0 51 0 0
#> 200.1 24.00 0 64 0 0
#> 196 24.00 0 19 0 0
#> 152 24.00 0 36 0 1
#> 62 24.00 0 71 0 0
#> 54 24.00 0 53 1 0
#> 131 24.00 0 66 0 0
#> 163 24.00 0 66 0 0
#> 2 24.00 0 9 0 0
#> 143 24.00 0 51 0 0
#> 104 24.00 0 50 1 0
#> 142 24.00 0 53 0 0
#> 142.1 24.00 0 53 0 0
#> 95 24.00 0 68 0 1
#> 71 24.00 0 51 0 0
#> 178 24.00 0 52 1 0
#> 54.1 24.00 0 53 1 0
#> 7 24.00 0 37 1 0
#> 132 24.00 0 55 0 0
#> 178.1 24.00 0 52 1 0
#> 121 24.00 0 57 1 0
#> 178.2 24.00 0 52 1 0
#> 142.2 24.00 0 53 0 0
#> 131.1 24.00 0 66 0 0
#> 94 24.00 0 51 0 1
#> 7.1 24.00 0 37 1 0
#> 200.2 24.00 0 64 0 0
#> 65 24.00 0 57 1 0
#> 87 24.00 0 27 0 0
#> 146 24.00 0 63 1 0
#> 176 24.00 0 43 0 1
#> 72 24.00 0 40 0 1
#> 27 24.00 0 63 1 0
#> 104.1 24.00 0 50 1 0
#> 118 24.00 0 44 1 0
#> 151.1 24.00 0 42 0 0
#> 19 24.00 0 57 0 1
#> 151.2 24.00 0 42 0 0
#> 141.1 24.00 0 44 1 0
#> 7.2 24.00 0 37 1 0
#> 112.1 24.00 0 61 0 0
#> 185 24.00 0 44 1 0
#> 151.3 24.00 0 42 0 0
#> 46 24.00 0 71 0 0
#> 47 24.00 0 38 0 1
#> 186.1 24.00 0 45 1 0
#> 142.3 24.00 0 53 0 0
#> 7.3 24.00 0 37 1 0
#> 46.1 24.00 0 71 0 0
#> 2.1 24.00 0 9 0 0
#> 2.2 24.00 0 9 0 0
#> 156 24.00 0 50 1 0
#> 147 24.00 0 76 1 0
#> 200.3 24.00 0 64 0 0
#> 165 24.00 0 47 0 0
#> 161 24.00 0 45 0 0
#> 47.1 24.00 0 38 0 1
#> 54.2 24.00 0 53 1 0
#> 137 24.00 0 45 1 0
#> 185.1 24.00 0 44 1 0
#> 196.1 24.00 0 19 0 0
#> 48 24.00 0 31 1 0
#> 1 24.00 0 23 1 0
#> 185.2 24.00 0 44 1 0
#> 28.1 24.00 0 67 1 0
#> 11 24.00 0 42 0 1
#> 132.1 24.00 0 55 0 0
#> 152.1 24.00 0 36 0 1
#> 35 24.00 0 51 0 0
#> 87.1 24.00 0 27 0 0
#> 65.1 24.00 0 57 1 0
#> 104.2 24.00 0 50 1 0
#> 12 24.00 0 63 0 0
#> 35.1 24.00 0 51 0 0
#> 35.2 24.00 0 51 0 0
#> 82 24.00 0 34 0 0
#> 172 24.00 0 41 0 0
#> 121.1 24.00 0 57 1 0
#> 163.1 24.00 0 66 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.475 NA NA NA
#> 2 age, Cure model -0.0107 NA NA NA
#> 3 grade_ii, Cure model -0.145 NA NA NA
#> 4 grade_iii, Cure model 1.16 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0108 NA NA NA
#> 2 grade_ii, Survival model 0.320 NA NA NA
#> 3 grade_iii, Survival model 0.438 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.47465 -0.01069 -0.14456 1.16125
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.8
#> Residual Deviance: 252.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.47464945 -0.01068671 -0.14455562 1.16124680
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01079619 0.31977637 0.43803346
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.430306188 0.784438057 0.879762217 0.939937675 0.150178758 0.009026577
#> [7] 0.430306188 0.001839281 0.749275762 0.612913013 0.749275762 0.018321835
#> [13] 0.843622369 0.075404615 0.090087305 0.030772508 0.358979993 0.290743993
#> [19] 0.657896063 0.217513477 0.166060166 0.691781321 0.348968884 0.927852800
#> [25] 0.263158338 0.808148141 0.691781321 0.461074576 0.111859874 0.492519254
#> [31] 0.772670448 0.300352089 0.134949521 0.043142254 0.524948229 0.150178758
#> [37] 0.191228718 0.657896063 0.939937675 0.036948519 0.379261262 0.082632902
#> [43] 0.796251021 0.557145784 0.379261262 0.726077995 0.329308895 0.855656438
#> [49] 0.127051089 0.524948229 0.987852214 0.691781321 0.263158338 0.855656438
#> [55] 0.226436289 0.612913013 0.043142254 0.579255817 0.503257017 0.358979993
#> [61] 0.461074576 0.808148141 0.601624836 0.524948229 0.612913013 0.319660689
#> [67] 0.657896063 0.235489181 0.001839281 0.915811837 0.134949521 0.514048072
#> [73] 0.166060166 0.568163840 0.612913013 0.090087305 0.253796743 0.430306188
#> [79] 0.379261262 0.199886312 0.461074576 0.409728977 0.891918286 0.329308895
#> [85] 0.009026577 0.001839281 0.111859874 0.263158338 0.726077995 0.062091644
#> [91] 0.975733923 0.310031986 0.891918286 0.182581313 0.024366502 0.808148141
#> [97] 0.590420324 0.939937675 0.090087305 0.043142254 0.062091644 0.208674755
#> [103] 0.235489181 0.409728977 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 130 37 52 70 150 168 130.1 78 140 180 140.1 164 107
#> 16.47 12.52 10.42 7.38 20.33 23.72 16.47 23.88 12.68 14.82 12.68 23.60 11.18
#> 175 153 69 23 184 96 97 166 155 45 16 134 43
#> 21.91 21.33 23.23 16.92 17.77 14.54 19.14 19.98 13.08 17.42 8.71 17.81 12.10
#> 155.1 85 32 5 154 110 128 15 26 150.1 170 96.1 70.1
#> 13.08 16.44 20.90 16.43 12.63 17.56 20.35 22.68 15.77 20.33 19.54 14.54 7.38
#> 63 106 197 56 125 106.1 14 30 10 190 26.1 91 155.2
#> 22.77 16.67 21.60 12.21 15.65 16.67 12.89 17.43 10.53 20.81 15.77 5.33 13.08
#> 134.1 10.1 179 180.1 15.1 29 79 23.1 85.1 43.1 157 26.2 180.2
#> 17.81 10.53 18.63 14.82 22.68 15.45 16.23 16.92 16.44 12.10 15.10 15.77 14.82
#> 111 96.2 88 78.1 187 128.1 100 166.1 6 180.3 153.1 41 130.2
#> 17.45 14.54 18.37 23.88 9.92 20.35 16.07 19.98 15.64 14.82 21.33 18.02 16.47
#> 106.2 58 85.2 171 101 30.1 168.1 78.2 32.1 134.2 14.1 194 77
#> 16.67 19.34 16.44 16.57 9.97 17.43 23.72 23.88 20.90 17.81 12.89 22.40 7.27
#> 117 101.1 105 129 43.2 18 70.2 153.2 15.2 194.1 76 88.1 171.1
#> 17.46 9.97 19.75 23.41 12.10 15.21 7.38 21.33 22.68 22.40 19.22 18.37 16.57
#> 186 174 28 67 200 120 151 141 112 162 200.1 196 152
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62 54 131 163 2 143 104 142 142.1 95 71 178 54.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 7 132 178.1 121 178.2 142.2 131.1 94 7.1 200.2 65 87 146
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176 72 27 104.1 118 151.1 19 151.2 141.1 7.2 112.1 185 151.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 46 47 186.1 142.3 7.3 46.1 2.1 2.2 156 147 200.3 165 161
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 47.1 54.2 137 185.1 196.1 48 1 185.2 28.1 11 132.1 152.1 35
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87.1 65.1 104.2 12 35.1 35.2 82 172 121.1 163.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[21]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.004643256 0.493759546 0.507734176
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.03554477 0.01396553 0.52091469
#> grade_iii, Cure model
#> 1.46991817
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 97 19.14 1 65 0 1
#> 52 10.42 1 52 0 1
#> 125 15.65 1 67 1 0
#> 145 10.07 1 65 1 0
#> 100 16.07 1 60 0 0
#> 23 16.92 1 61 0 0
#> 36 21.19 1 48 0 1
#> 128 20.35 1 35 0 1
#> 100.1 16.07 1 60 0 0
#> 129 23.41 1 53 1 0
#> 179 18.63 1 42 0 0
#> 99 21.19 1 38 0 1
#> 108 18.29 1 39 0 1
#> 171 16.57 1 41 0 1
#> 180 14.82 1 37 0 0
#> 66 22.13 1 53 0 0
#> 133 14.65 1 57 0 0
#> 51 18.23 1 83 0 1
#> 18 15.21 1 49 1 0
#> 111 17.45 1 47 0 1
#> 58 19.34 1 39 0 0
#> 170 19.54 1 43 0 1
#> 158 20.14 1 74 1 0
#> 13 14.34 1 54 0 1
#> 136 21.83 1 43 0 1
#> 123 13.00 1 44 1 0
#> 26 15.77 1 49 0 1
#> 169 22.41 1 46 0 0
#> 16 8.71 1 71 0 1
#> 139 21.49 1 63 1 0
#> 179.1 18.63 1 42 0 0
#> 13.1 14.34 1 54 0 1
#> 69 23.23 1 25 0 1
#> 41 18.02 1 40 1 0
#> 78 23.88 1 43 0 0
#> 175 21.91 1 43 0 0
#> 51.1 18.23 1 83 0 1
#> 187 9.92 1 39 1 0
#> 58.1 19.34 1 39 0 0
#> 91 5.33 1 61 0 1
#> 61 10.12 1 36 0 1
#> 159 10.55 1 50 0 1
#> 14 12.89 1 21 0 0
#> 154 12.63 1 20 1 0
#> 24 23.89 1 38 0 0
#> 130 16.47 1 53 0 1
#> 159.1 10.55 1 50 0 1
#> 86 23.81 1 58 0 1
#> 15 22.68 1 48 0 0
#> 130.1 16.47 1 53 0 1
#> 111.1 17.45 1 47 0 1
#> 129.1 23.41 1 53 1 0
#> 4 17.64 1 NA 0 1
#> 125.1 15.65 1 67 1 0
#> 134 17.81 1 47 1 0
#> 195 11.76 1 NA 1 0
#> 77 7.27 1 67 0 1
#> 192 16.44 1 31 1 0
#> 37 12.52 1 57 1 0
#> 41.1 18.02 1 40 1 0
#> 37.1 12.52 1 57 1 0
#> 26.1 15.77 1 49 0 1
#> 6 15.64 1 39 0 0
#> 179.2 18.63 1 42 0 0
#> 184 17.77 1 38 0 0
#> 5 16.43 1 51 0 1
#> 199 19.81 1 NA 0 1
#> 8 18.43 1 32 0 0
#> 189 10.51 1 NA 1 0
#> 124 9.73 1 NA 1 0
#> 167 15.55 1 56 1 0
#> 63 22.77 1 31 1 0
#> 37.2 12.52 1 57 1 0
#> 158.1 20.14 1 74 1 0
#> 14.1 12.89 1 21 0 0
#> 57 14.46 1 45 0 1
#> 58.2 19.34 1 39 0 0
#> 36.1 21.19 1 48 0 1
#> 177 12.53 1 75 0 0
#> 69.1 23.23 1 25 0 1
#> 166 19.98 1 48 0 0
#> 101 9.97 1 10 0 1
#> 63.1 22.77 1 31 1 0
#> 117 17.46 1 26 0 1
#> 194 22.40 1 38 0 1
#> 51.2 18.23 1 83 0 1
#> 25 6.32 1 34 1 0
#> 78.1 23.88 1 43 0 0
#> 52.1 10.42 1 52 0 1
#> 123.1 13.00 1 44 1 0
#> 187.1 9.92 1 39 1 0
#> 36.2 21.19 1 48 0 1
#> 179.3 18.63 1 42 0 0
#> 130.2 16.47 1 53 0 1
#> 70 7.38 1 30 1 0
#> 91.1 5.33 1 61 0 1
#> 97.1 19.14 1 65 0 1
#> 96 14.54 1 33 0 1
#> 85 16.44 1 36 0 0
#> 125.2 15.65 1 67 1 0
#> 18.1 15.21 1 49 1 0
#> 153 21.33 1 55 1 0
#> 101.1 9.97 1 10 0 1
#> 15.1 22.68 1 48 0 0
#> 187.2 9.92 1 39 1 0
#> 117.1 17.46 1 26 0 1
#> 77.1 7.27 1 67 0 1
#> 150 20.33 1 48 0 0
#> 42 12.43 1 49 0 1
#> 23.1 16.92 1 61 0 0
#> 61.1 10.12 1 36 0 1
#> 90 20.94 1 50 0 1
#> 35 24.00 0 51 0 0
#> 151 24.00 0 42 0 0
#> 71 24.00 0 51 0 0
#> 54 24.00 0 53 1 0
#> 120 24.00 0 68 0 1
#> 122 24.00 0 66 0 0
#> 67 24.00 0 25 0 0
#> 196 24.00 0 19 0 0
#> 75 24.00 0 21 1 0
#> 53 24.00 0 32 0 1
#> 151.1 24.00 0 42 0 0
#> 74 24.00 0 43 0 1
#> 3 24.00 0 31 1 0
#> 196.1 24.00 0 19 0 0
#> 17 24.00 0 38 0 1
#> 44 24.00 0 56 0 0
#> 185 24.00 0 44 1 0
#> 84 24.00 0 39 0 1
#> 47 24.00 0 38 0 1
#> 160 24.00 0 31 1 0
#> 67.1 24.00 0 25 0 0
#> 137 24.00 0 45 1 0
#> 141 24.00 0 44 1 0
#> 65 24.00 0 57 1 0
#> 80 24.00 0 41 0 0
#> 191 24.00 0 60 0 1
#> 141.1 24.00 0 44 1 0
#> 161 24.00 0 45 0 0
#> 172 24.00 0 41 0 0
#> 27 24.00 0 63 1 0
#> 33 24.00 0 53 0 0
#> 54.1 24.00 0 53 1 0
#> 196.2 24.00 0 19 0 0
#> 11 24.00 0 42 0 1
#> 115 24.00 0 NA 1 0
#> 64 24.00 0 43 0 0
#> 144 24.00 0 28 0 1
#> 12 24.00 0 63 0 0
#> 116 24.00 0 58 0 1
#> 109 24.00 0 48 0 0
#> 148 24.00 0 61 1 0
#> 142 24.00 0 53 0 0
#> 103 24.00 0 56 1 0
#> 126 24.00 0 48 0 0
#> 72 24.00 0 40 0 1
#> 87 24.00 0 27 0 0
#> 72.1 24.00 0 40 0 1
#> 163 24.00 0 66 0 0
#> 3.1 24.00 0 31 1 0
#> 143 24.00 0 51 0 0
#> 2 24.00 0 9 0 0
#> 48 24.00 0 31 1 0
#> 67.2 24.00 0 25 0 0
#> 126.1 24.00 0 48 0 0
#> 44.1 24.00 0 56 0 0
#> 84.1 24.00 0 39 0 1
#> 163.1 24.00 0 66 0 0
#> 185.1 24.00 0 44 1 0
#> 82 24.00 0 34 0 0
#> 62 24.00 0 71 0 0
#> 112 24.00 0 61 0 0
#> 46 24.00 0 71 0 0
#> 118 24.00 0 44 1 0
#> 165 24.00 0 47 0 0
#> 161.1 24.00 0 45 0 0
#> 156 24.00 0 50 1 0
#> 44.2 24.00 0 56 0 0
#> 12.1 24.00 0 63 0 0
#> 172.1 24.00 0 41 0 0
#> 82.1 24.00 0 34 0 0
#> 3.2 24.00 0 31 1 0
#> 151.2 24.00 0 42 0 0
#> 103.1 24.00 0 56 1 0
#> 151.3 24.00 0 42 0 0
#> 118.1 24.00 0 44 1 0
#> 87.1 24.00 0 27 0 0
#> 104 24.00 0 50 1 0
#> 172.2 24.00 0 41 0 0
#> 172.3 24.00 0 41 0 0
#> 38 24.00 0 31 1 0
#> 178 24.00 0 52 1 0
#> 20 24.00 0 46 1 0
#> 161.2 24.00 0 45 0 0
#> 173 24.00 0 19 0 1
#> 120.1 24.00 0 68 0 1
#> 65.1 24.00 0 57 1 0
#> 200 24.00 0 64 0 0
#> 53.1 24.00 0 32 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.04 NA NA NA
#> 2 age, Cure model 0.0140 NA NA NA
#> 3 grade_ii, Cure model 0.521 NA NA NA
#> 4 grade_iii, Cure model 1.47 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00464 NA NA NA
#> 2 grade_ii, Survival model 0.494 NA NA NA
#> 3 grade_iii, Survival model 0.508 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.03554 0.01397 0.52091 1.46992
#>
#> Degrees of Freedom: 193 Total (i.e. Null); 190 Residual
#> Null Deviance: 266.9
#> Residual Deviance: 248.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.03554477 0.01396553 0.52091469 1.46991817
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.004643256 0.493759546 0.507734176
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.52101343 0.91016890 0.76048935 0.93207391 0.73401408 0.67171240
#> [7] 0.38679121 0.43736404 0.73401408 0.16866206 0.53821394 0.38679121
#> [13] 0.58013276 0.68605988 0.80450446 0.32300680 0.81070031 0.58852955
#> [19] 0.79214270 0.65726389 0.49433816 0.48518171 0.45726167 0.82911033
#> [25] 0.34978448 0.84104816 0.74737901 0.29518168 0.96399737 0.36261174
#> [31] 0.53821394 0.82911033 0.20599926 0.61193758 0.08190534 0.33645447
#> [37] 0.58852955 0.94821774 0.49433816 0.98989033 0.92118416 0.89900294
#> [43] 0.85281730 0.86456983 0.03542148 0.69319577 0.89900294 0.14199321
#> [49] 0.26711395 0.69319577 0.65726389 0.16866206 0.76048935 0.62726155
#> [55] 0.97447454 0.71367948 0.87628233 0.61193758 0.87628233 0.74737901
#> [61] 0.77946583 0.53821394 0.63487379 0.72726123 0.57161374 0.78583302
#> [67] 0.23829373 0.87628233 0.45726167 0.85281730 0.82301988 0.49433816
#> [73] 0.38679121 0.87043429 0.20599926 0.47584399 0.93749616 0.23829373
#> [79] 0.64246846 0.30940120 0.58852955 0.98475919 0.08190534 0.91016890
#> [85] 0.84104816 0.94821774 0.38679121 0.53821394 0.69319577 0.96924846
#> [91] 0.98989033 0.52101343 0.81688185 0.71367948 0.76048935 0.79214270
#> [97] 0.37491874 0.93749616 0.26711395 0.94821774 0.64246846 0.97447454
#> [103] 0.44734047 0.89332500 0.67171240 0.92118416 0.42716554 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [193] 0.00000000 0.00000000
#>
#> $Time
#> 97 52 125 145 100 23 36 128 100.1 129 179 99 108
#> 19.14 10.42 15.65 10.07 16.07 16.92 21.19 20.35 16.07 23.41 18.63 21.19 18.29
#> 171 180 66 133 51 18 111 58 170 158 13 136 123
#> 16.57 14.82 22.13 14.65 18.23 15.21 17.45 19.34 19.54 20.14 14.34 21.83 13.00
#> 26 169 16 139 179.1 13.1 69 41 78 175 51.1 187 58.1
#> 15.77 22.41 8.71 21.49 18.63 14.34 23.23 18.02 23.88 21.91 18.23 9.92 19.34
#> 91 61 159 14 154 24 130 159.1 86 15 130.1 111.1 129.1
#> 5.33 10.12 10.55 12.89 12.63 23.89 16.47 10.55 23.81 22.68 16.47 17.45 23.41
#> 125.1 134 77 192 37 41.1 37.1 26.1 6 179.2 184 5 8
#> 15.65 17.81 7.27 16.44 12.52 18.02 12.52 15.77 15.64 18.63 17.77 16.43 18.43
#> 167 63 37.2 158.1 14.1 57 58.2 36.1 177 69.1 166 101 63.1
#> 15.55 22.77 12.52 20.14 12.89 14.46 19.34 21.19 12.53 23.23 19.98 9.97 22.77
#> 117 194 51.2 25 78.1 52.1 123.1 187.1 36.2 179.3 130.2 70 91.1
#> 17.46 22.40 18.23 6.32 23.88 10.42 13.00 9.92 21.19 18.63 16.47 7.38 5.33
#> 97.1 96 85 125.2 18.1 153 101.1 15.1 187.2 117.1 77.1 150 42
#> 19.14 14.54 16.44 15.65 15.21 21.33 9.97 22.68 9.92 17.46 7.27 20.33 12.43
#> 23.1 61.1 90 35 151 71 54 120 122 67 196 75 53
#> 16.92 10.12 20.94 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 151.1 74 3 196.1 17 44 185 84 47 160 67.1 137 141
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 65 80 191 141.1 161 172 27 33 54.1 196.2 11 64 144
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12 116 109 148 142 103 126 72 87 72.1 163 3.1 143
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 2 48 67.2 126.1 44.1 84.1 163.1 185.1 82 62 112 46 118
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165 161.1 156 44.2 12.1 172.1 82.1 3.2 151.2 103.1 151.3 118.1 87.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 104 172.2 172.3 38 178 20 161.2 173 120.1 65.1 200 53.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[22]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.003534422 0.665967321 0.219113026
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.51803492 0.02071342 0.50258689
#> grade_iii, Cure model
#> 1.91321851
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 192 16.44 1 31 1 0
#> 164 23.60 1 76 0 1
#> 26 15.77 1 49 0 1
#> 114 13.68 1 NA 0 0
#> 107 11.18 1 54 1 0
#> 180 14.82 1 37 0 0
#> 106 16.67 1 49 1 0
#> 171 16.57 1 41 0 1
#> 128 20.35 1 35 0 1
#> 77 7.27 1 67 0 1
#> 16 8.71 1 71 0 1
#> 90 20.94 1 50 0 1
#> 51 18.23 1 83 0 1
#> 177 12.53 1 75 0 0
#> 159 10.55 1 50 0 1
#> 188 16.16 1 46 0 1
#> 15 22.68 1 48 0 0
#> 153 21.33 1 55 1 0
#> 164.1 23.60 1 76 0 1
#> 6 15.64 1 39 0 0
#> 18 15.21 1 49 1 0
#> 197 21.60 1 69 1 0
#> 130 16.47 1 53 0 1
#> 187 9.92 1 39 1 0
#> 36 21.19 1 48 0 1
#> 169 22.41 1 46 0 0
#> 101 9.97 1 10 0 1
#> 114.1 13.68 1 NA 0 0
#> 10 10.53 1 34 0 0
#> 29 15.45 1 68 1 0
#> 60 13.15 1 38 1 0
#> 70 7.38 1 30 1 0
#> 177.1 12.53 1 75 0 0
#> 117 17.46 1 26 0 1
#> 140 12.68 1 59 1 0
#> 90.1 20.94 1 50 0 1
#> 100 16.07 1 60 0 0
#> 157 15.10 1 47 0 0
#> 117.1 17.46 1 26 0 1
#> 106.1 16.67 1 49 1 0
#> 37 12.52 1 57 1 0
#> 66 22.13 1 53 0 0
#> 49 12.19 1 48 1 0
#> 42 12.43 1 49 0 1
#> 45 17.42 1 54 0 1
#> 124 9.73 1 NA 1 0
#> 190 20.81 1 42 1 0
#> 145 10.07 1 65 1 0
#> 6.1 15.64 1 39 0 0
#> 164.2 23.60 1 76 0 1
#> 30 17.43 1 78 0 0
#> 96 14.54 1 33 0 1
#> 77.1 7.27 1 67 0 1
#> 110 17.56 1 65 0 1
#> 91 5.33 1 61 0 1
#> 108 18.29 1 39 0 1
#> 149 8.37 1 33 1 0
#> 78 23.88 1 43 0 0
#> 124.1 9.73 1 NA 1 0
#> 42.1 12.43 1 49 0 1
#> 42.2 12.43 1 49 0 1
#> 153.1 21.33 1 55 1 0
#> 100.1 16.07 1 60 0 0
#> 149.1 8.37 1 33 1 0
#> 90.2 20.94 1 50 0 1
#> 133 14.65 1 57 0 0
#> 8 18.43 1 32 0 0
#> 29.1 15.45 1 68 1 0
#> 40 18.00 1 28 1 0
#> 108.1 18.29 1 39 0 1
#> 188.1 16.16 1 46 0 1
#> 92 22.92 1 47 0 1
#> 76 19.22 1 54 0 1
#> 56 12.21 1 60 0 0
#> 61 10.12 1 36 0 1
#> 97 19.14 1 65 0 1
#> 40.1 18.00 1 28 1 0
#> 145.1 10.07 1 65 1 0
#> 42.3 12.43 1 49 0 1
#> 128.1 20.35 1 35 0 1
#> 127 3.53 1 62 0 1
#> 99 21.19 1 38 0 1
#> 145.2 10.07 1 65 1 0
#> 8.1 18.43 1 32 0 0
#> 106.2 16.67 1 49 1 0
#> 58 19.34 1 39 0 0
#> 4 17.64 1 NA 0 1
#> 192.1 16.44 1 31 1 0
#> 29.2 15.45 1 68 1 0
#> 23 16.92 1 61 0 0
#> 69 23.23 1 25 0 1
#> 179 18.63 1 42 0 0
#> 51.1 18.23 1 83 0 1
#> 88 18.37 1 47 0 0
#> 45.1 17.42 1 54 0 1
#> 168 23.72 1 70 0 0
#> 91.1 5.33 1 61 0 1
#> 32 20.90 1 37 1 0
#> 170 19.54 1 43 0 1
#> 58.1 19.34 1 39 0 0
#> 145.3 10.07 1 65 1 0
#> 15.1 22.68 1 48 0 0
#> 199 19.81 1 NA 0 1
#> 30.1 17.43 1 78 0 0
#> 90.3 20.94 1 50 0 1
#> 190.1 20.81 1 42 1 0
#> 110.1 17.56 1 65 0 1
#> 26.1 15.77 1 49 0 1
#> 192.2 16.44 1 31 1 0
#> 5 16.43 1 51 0 1
#> 29.3 15.45 1 68 1 0
#> 96.1 14.54 1 33 0 1
#> 104 24.00 0 50 1 0
#> 11 24.00 0 42 0 1
#> 48 24.00 0 31 1 0
#> 126 24.00 0 48 0 0
#> 19 24.00 0 57 0 1
#> 112 24.00 0 61 0 0
#> 119 24.00 0 17 0 0
#> 46 24.00 0 71 0 0
#> 144 24.00 0 28 0 1
#> 44 24.00 0 56 0 0
#> 152 24.00 0 36 0 1
#> 44.1 24.00 0 56 0 0
#> 165 24.00 0 47 0 0
#> 126.1 24.00 0 48 0 0
#> 173 24.00 0 19 0 1
#> 182 24.00 0 35 0 0
#> 7 24.00 0 37 1 0
#> 87 24.00 0 27 0 0
#> 160 24.00 0 31 1 0
#> 116 24.00 0 58 0 1
#> 98 24.00 0 34 1 0
#> 83 24.00 0 6 0 0
#> 98.1 24.00 0 34 1 0
#> 12 24.00 0 63 0 0
#> 165.1 24.00 0 47 0 0
#> 73 24.00 0 NA 0 1
#> 142 24.00 0 53 0 0
#> 98.2 24.00 0 34 1 0
#> 186 24.00 0 45 1 0
#> 28 24.00 0 67 1 0
#> 74 24.00 0 43 0 1
#> 12.1 24.00 0 63 0 0
#> 54 24.00 0 53 1 0
#> 35 24.00 0 51 0 0
#> 44.2 24.00 0 56 0 0
#> 2 24.00 0 9 0 0
#> 135 24.00 0 58 1 0
#> 7.1 24.00 0 37 1 0
#> 112.1 24.00 0 61 0 0
#> 27 24.00 0 63 1 0
#> 112.2 24.00 0 61 0 0
#> 163 24.00 0 66 0 0
#> 62 24.00 0 71 0 0
#> 191 24.00 0 60 0 1
#> 142.1 24.00 0 53 0 0
#> 46.1 24.00 0 71 0 0
#> 160.1 24.00 0 31 1 0
#> 161 24.00 0 45 0 0
#> 152.1 24.00 0 36 0 1
#> 35.1 24.00 0 51 0 0
#> 141 24.00 0 44 1 0
#> 160.2 24.00 0 31 1 0
#> 112.3 24.00 0 61 0 0
#> 103 24.00 0 56 1 0
#> 172 24.00 0 41 0 0
#> 71 24.00 0 51 0 0
#> 22 24.00 0 52 1 0
#> 160.3 24.00 0 31 1 0
#> 3 24.00 0 31 1 0
#> 103.1 24.00 0 56 1 0
#> 12.2 24.00 0 63 0 0
#> 151 24.00 0 42 0 0
#> 65 24.00 0 57 1 0
#> 65.1 24.00 0 57 1 0
#> 3.1 24.00 0 31 1 0
#> 109 24.00 0 48 0 0
#> 156 24.00 0 50 1 0
#> 118 24.00 0 44 1 0
#> 46.2 24.00 0 71 0 0
#> 28.1 24.00 0 67 1 0
#> 142.2 24.00 0 53 0 0
#> 84 24.00 0 39 0 1
#> 120 24.00 0 68 0 1
#> 160.4 24.00 0 31 1 0
#> 67 24.00 0 25 0 0
#> 1 24.00 0 23 1 0
#> 156.1 24.00 0 50 1 0
#> 121 24.00 0 57 1 0
#> 178 24.00 0 52 1 0
#> 35.2 24.00 0 51 0 0
#> 17 24.00 0 38 0 1
#> 1.1 24.00 0 23 1 0
#> 132 24.00 0 55 0 0
#> 1.2 24.00 0 23 1 0
#> 126.2 24.00 0 48 0 0
#> 163.1 24.00 0 66 0 0
#> 143 24.00 0 51 0 0
#> 80 24.00 0 41 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.52 NA NA NA
#> 2 age, Cure model 0.0207 NA NA NA
#> 3 grade_ii, Cure model 0.503 NA NA NA
#> 4 grade_iii, Cure model 1.91 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00353 NA NA NA
#> 2 grade_ii, Survival model 0.666 NA NA NA
#> 3 grade_iii, Survival model 0.219 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.51803 0.02071 0.50259 1.91322
#>
#> Degrees of Freedom: 192 Total (i.e. Null); 189 Residual
#> Null Deviance: 265.7
#> Residual Deviance: 237.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.51803492 0.02071342 0.50258689 1.91321851
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.003534422 0.665967321 0.219113026
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.559500158 0.032489916 0.630256887 0.845178661 0.717331290 0.513596421
#> [7] 0.540966373 0.262839291 0.960024123 0.927755109 0.192802055 0.389657015
#> [13] 0.769069144 0.853596165 0.594798943 0.087822738 0.149640866 0.032489916
#> [19] 0.648011403 0.700029324 0.137262009 0.550235784 0.919582383 0.171314135
#> [25] 0.111505124 0.911358807 0.862010077 0.665828805 0.751929185 0.952003993
#> [31] 0.769069144 0.447139809 0.760527169 0.192802055 0.612478869 0.708672225
#> [37] 0.447139809 0.513596421 0.786146071 0.124269084 0.836709861 0.794676339
#> [43] 0.484981454 0.243495041 0.878848686 0.648011403 0.032489916 0.465968035
#> [49] 0.734694029 0.960024123 0.428203543 0.976002051 0.370108394 0.935930093
#> [55] 0.005512245 0.794676339 0.794676339 0.149640866 0.612478869 0.935930093
#> [61] 0.192802055 0.726003188 0.340609278 0.665828805 0.409276258 0.370108394
#> [67] 0.594798943 0.075627671 0.311123785 0.828185615 0.870433299 0.320936695
#> [73] 0.409276258 0.878848686 0.794676339 0.262839291 0.991979064 0.171314135
#> [79] 0.878848686 0.340609278 0.513596421 0.291790324 0.559500158 0.665828805
#> [85] 0.503973633 0.063329290 0.330752800 0.389657015 0.360156512 0.484981454
#> [91] 0.017656589 0.976002051 0.233049145 0.282042753 0.291790324 0.878848686
#> [97] 0.087822738 0.465968035 0.192802055 0.243495041 0.428203543 0.630256887
#> [103] 0.559500158 0.585876775 0.665828805 0.734694029 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [193] 0.000000000
#>
#> $Time
#> 192 164 26 107 180 106 171 128 77 16 90 51 177
#> 16.44 23.60 15.77 11.18 14.82 16.67 16.57 20.35 7.27 8.71 20.94 18.23 12.53
#> 159 188 15 153 164.1 6 18 197 130 187 36 169 101
#> 10.55 16.16 22.68 21.33 23.60 15.64 15.21 21.60 16.47 9.92 21.19 22.41 9.97
#> 10 29 60 70 177.1 117 140 90.1 100 157 117.1 106.1 37
#> 10.53 15.45 13.15 7.38 12.53 17.46 12.68 20.94 16.07 15.10 17.46 16.67 12.52
#> 66 49 42 45 190 145 6.1 164.2 30 96 77.1 110 91
#> 22.13 12.19 12.43 17.42 20.81 10.07 15.64 23.60 17.43 14.54 7.27 17.56 5.33
#> 108 149 78 42.1 42.2 153.1 100.1 149.1 90.2 133 8 29.1 40
#> 18.29 8.37 23.88 12.43 12.43 21.33 16.07 8.37 20.94 14.65 18.43 15.45 18.00
#> 108.1 188.1 92 76 56 61 97 40.1 145.1 42.3 128.1 127 99
#> 18.29 16.16 22.92 19.22 12.21 10.12 19.14 18.00 10.07 12.43 20.35 3.53 21.19
#> 145.2 8.1 106.2 58 192.1 29.2 23 69 179 51.1 88 45.1 168
#> 10.07 18.43 16.67 19.34 16.44 15.45 16.92 23.23 18.63 18.23 18.37 17.42 23.72
#> 91.1 32 170 58.1 145.3 15.1 30.1 90.3 190.1 110.1 26.1 192.2 5
#> 5.33 20.90 19.54 19.34 10.07 22.68 17.43 20.94 20.81 17.56 15.77 16.44 16.43
#> 29.3 96.1 104 11 48 126 19 112 119 46 144 44 152
#> 15.45 14.54 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44.1 165 126.1 173 182 7 87 160 116 98 83 98.1 12
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165.1 142 98.2 186 28 74 12.1 54 35 44.2 2 135 7.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 112.1 27 112.2 163 62 191 142.1 46.1 160.1 161 152.1 35.1 141
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 160.2 112.3 103 172 71 22 160.3 3 103.1 12.2 151 65 65.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3.1 109 156 118 46.2 28.1 142.2 84 120 160.4 67 1 156.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 121 178 35.2 17 1.1 132 1.2 126.2 163.1 143 80
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[23]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.007902316 0.752264671 0.541141177
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.51491285 0.01553086 -0.34835080
#> grade_iii, Cure model
#> 0.48267907
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 188 16.16 1 46 0 1
#> 125 15.65 1 67 1 0
#> 36 21.19 1 48 0 1
#> 130 16.47 1 53 0 1
#> 39 15.59 1 37 0 1
#> 125.1 15.65 1 67 1 0
#> 6 15.64 1 39 0 0
#> 30 17.43 1 78 0 0
#> 129 23.41 1 53 1 0
#> 96 14.54 1 33 0 1
#> 180 14.82 1 37 0 0
#> 52 10.42 1 52 0 1
#> 127 3.53 1 62 0 1
#> 150 20.33 1 48 0 0
#> 171 16.57 1 41 0 1
#> 32 20.90 1 37 1 0
#> 145 10.07 1 65 1 0
#> 25 6.32 1 34 1 0
#> 78 23.88 1 43 0 0
#> 179 18.63 1 42 0 0
#> 60 13.15 1 38 1 0
#> 107 11.18 1 54 1 0
#> 78.1 23.88 1 43 0 0
#> 107.1 11.18 1 54 1 0
#> 39.1 15.59 1 37 0 1
#> 96.1 14.54 1 33 0 1
#> 5 16.43 1 51 0 1
#> 183 9.24 1 67 1 0
#> 14 12.89 1 21 0 0
#> 107.2 11.18 1 54 1 0
#> 70 7.38 1 30 1 0
#> 76 19.22 1 54 0 1
#> 60.1 13.15 1 38 1 0
#> 184 17.77 1 38 0 0
#> 37 12.52 1 57 1 0
#> 107.3 11.18 1 54 1 0
#> 24 23.89 1 38 0 0
#> 128 20.35 1 35 0 1
#> 133 14.65 1 57 0 0
#> 61 10.12 1 36 0 1
#> 10 10.53 1 34 0 0
#> 100 16.07 1 60 0 0
#> 187 9.92 1 39 1 0
#> 92 22.92 1 47 0 1
#> 90 20.94 1 50 0 1
#> 59 10.16 1 NA 1 0
#> 110 17.56 1 65 0 1
#> 190 20.81 1 42 1 0
#> 5.1 16.43 1 51 0 1
#> 97 19.14 1 65 0 1
#> 105 19.75 1 60 0 0
#> 150.1 20.33 1 48 0 0
#> 177 12.53 1 75 0 0
#> 97.1 19.14 1 65 0 1
#> 15 22.68 1 48 0 0
#> 129.1 23.41 1 53 1 0
#> 89 11.44 1 NA 0 0
#> 24.1 23.89 1 38 0 0
#> 58 19.34 1 39 0 0
#> 192 16.44 1 31 1 0
#> 15.1 22.68 1 48 0 0
#> 49 12.19 1 48 1 0
#> 25.1 6.32 1 34 1 0
#> 58.1 19.34 1 39 0 0
#> 39.2 15.59 1 37 0 1
#> 60.2 13.15 1 38 1 0
#> 177.1 12.53 1 75 0 0
#> 10.1 10.53 1 34 0 0
#> 166 19.98 1 48 0 0
#> 139 21.49 1 63 1 0
#> 199 19.81 1 NA 0 1
#> 140 12.68 1 59 1 0
#> 36.1 21.19 1 48 0 1
#> 177.2 12.53 1 75 0 0
#> 88 18.37 1 47 0 0
#> 179.1 18.63 1 42 0 0
#> 13 14.34 1 54 0 1
#> 13.1 14.34 1 54 0 1
#> 189 10.51 1 NA 1 0
#> 4 17.64 1 NA 0 1
#> 105.1 19.75 1 60 0 0
#> 117 17.46 1 26 0 1
#> 139.1 21.49 1 63 1 0
#> 140.1 12.68 1 59 1 0
#> 106 16.67 1 49 1 0
#> 129.2 23.41 1 53 1 0
#> 89.1 11.44 1 NA 0 0
#> 25.2 6.32 1 34 1 0
#> 130.1 16.47 1 53 0 1
#> 90.1 20.94 1 50 0 1
#> 14.1 12.89 1 21 0 0
#> 110.1 17.56 1 65 0 1
#> 110.2 17.56 1 65 0 1
#> 127.1 3.53 1 62 0 1
#> 194 22.40 1 38 0 1
#> 77 7.27 1 67 0 1
#> 166.1 19.98 1 48 0 0
#> 111 17.45 1 47 0 1
#> 181 16.46 1 45 0 1
#> 154 12.63 1 20 1 0
#> 134 17.81 1 47 1 0
#> 188.1 16.16 1 46 0 1
#> 76.1 19.22 1 54 0 1
#> 49.1 12.19 1 48 1 0
#> 45 17.42 1 54 0 1
#> 180.1 14.82 1 37 0 0
#> 81 14.06 1 34 0 0
#> 25.3 6.32 1 34 1 0
#> 195 11.76 1 NA 1 0
#> 168 23.72 1 70 0 0
#> 113 22.86 1 34 0 0
#> 101 9.97 1 10 0 1
#> 156 24.00 0 50 1 0
#> 132 24.00 0 55 0 0
#> 27 24.00 0 63 1 0
#> 122 24.00 0 66 0 0
#> 137 24.00 0 45 1 0
#> 102 24.00 0 49 0 0
#> 144 24.00 0 28 0 1
#> 151 24.00 0 42 0 0
#> 119 24.00 0 17 0 0
#> 7 24.00 0 37 1 0
#> 84 24.00 0 39 0 1
#> 196 24.00 0 19 0 0
#> 87 24.00 0 27 0 0
#> 73 24.00 0 NA 0 1
#> 22 24.00 0 52 1 0
#> 46 24.00 0 71 0 0
#> 3 24.00 0 31 1 0
#> 118 24.00 0 44 1 0
#> 196.1 24.00 0 19 0 0
#> 82 24.00 0 34 0 0
#> 138 24.00 0 44 1 0
#> 144.1 24.00 0 28 0 1
#> 147 24.00 0 76 1 0
#> 163 24.00 0 66 0 0
#> 116 24.00 0 58 0 1
#> 174 24.00 0 49 1 0
#> 9 24.00 0 31 1 0
#> 19 24.00 0 57 0 1
#> 137.1 24.00 0 45 1 0
#> 27.1 24.00 0 63 1 0
#> 137.2 24.00 0 45 1 0
#> 20 24.00 0 46 1 0
#> 144.2 24.00 0 28 0 1
#> 118.1 24.00 0 44 1 0
#> 186 24.00 0 45 1 0
#> 9.1 24.00 0 31 1 0
#> 152 24.00 0 36 0 1
#> 71 24.00 0 51 0 0
#> 46.1 24.00 0 71 0 0
#> 126 24.00 0 48 0 0
#> 82.1 24.00 0 34 0 0
#> 131 24.00 0 66 0 0
#> 135 24.00 0 58 1 0
#> 98 24.00 0 34 1 0
#> 109 24.00 0 48 0 0
#> 148 24.00 0 61 1 0
#> 53 24.00 0 32 0 1
#> 137.3 24.00 0 45 1 0
#> 3.1 24.00 0 31 1 0
#> 198 24.00 0 66 0 1
#> 82.2 24.00 0 34 0 0
#> 71.1 24.00 0 51 0 0
#> 95 24.00 0 68 0 1
#> 9.2 24.00 0 31 1 0
#> 174.1 24.00 0 49 1 0
#> 115 24.00 0 NA 1 0
#> 53.1 24.00 0 32 0 1
#> 131.1 24.00 0 66 0 0
#> 11 24.00 0 42 0 1
#> 19.1 24.00 0 57 0 1
#> 103 24.00 0 56 1 0
#> 34 24.00 0 36 0 0
#> 11.1 24.00 0 42 0 1
#> 31 24.00 0 36 0 1
#> 178 24.00 0 52 1 0
#> 103.1 24.00 0 56 1 0
#> 38 24.00 0 31 1 0
#> 2 24.00 0 9 0 0
#> 9.3 24.00 0 31 1 0
#> 67 24.00 0 25 0 0
#> 102.1 24.00 0 49 0 0
#> 174.2 24.00 0 49 1 0
#> 67.1 24.00 0 25 0 0
#> 200 24.00 0 64 0 0
#> 198.1 24.00 0 66 0 1
#> 47 24.00 0 38 0 1
#> 132.1 24.00 0 55 0 0
#> 174.3 24.00 0 49 1 0
#> 135.1 24.00 0 58 1 0
#> 1 24.00 0 23 1 0
#> 126.1 24.00 0 48 0 0
#> 53.2 24.00 0 32 0 1
#> 38.1 24.00 0 31 1 0
#> 3.2 24.00 0 31 1 0
#> 178.1 24.00 0 52 1 0
#> 198.2 24.00 0 66 0 1
#> 118.2 24.00 0 44 1 0
#> 73.1 24.00 0 NA 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.515 NA NA NA
#> 2 age, Cure model 0.0155 NA NA NA
#> 3 grade_ii, Cure model -0.348 NA NA NA
#> 4 grade_iii, Cure model 0.483 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00790 NA NA NA
#> 2 grade_ii, Survival model 0.752 NA NA NA
#> 3 grade_iii, Survival model 0.541 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.51491 0.01553 -0.34835 0.48268
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 261.3
#> Residual Deviance: 253.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.51491285 0.01553086 -0.34835080 0.48267907
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.007902316 0.752264671 0.541141177
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.537251089 0.565761672 0.157403334 0.479305000 0.594196836 0.565761672
#> [7] 0.584639306 0.439408247 0.057521882 0.650427508 0.622037664 0.878331215
#> [13] 0.982985144 0.223897347 0.469423376 0.195921889 0.896265406 0.949219528
#> [19] 0.021679410 0.339627038 0.697356336 0.825191658 0.021679410 0.825191658
#> [25] 0.594196836 0.650427508 0.518209784 0.922903952 0.724694815 0.825191658
#> [31] 0.931713317 0.300412342 0.697356336 0.379790859 0.797872618 0.825191658
#> [37] 0.005618784 0.214727154 0.640883174 0.887311568 0.860437015 0.556162188
#> [43] 0.914073552 0.085066176 0.176826296 0.389920395 0.205436881 0.518209784
#> [49] 0.320036237 0.261215724 0.223897347 0.770470142 0.320036237 0.105675914
#> [55] 0.057521882 0.005618784 0.280632341 0.508546990 0.105675914 0.807075834
#> [61] 0.949219528 0.280632341 0.594196836 0.697356336 0.770470142 0.860437015
#> [67] 0.242329559 0.137553881 0.743108309 0.157403334 0.770470142 0.359542534
#> [73] 0.339627038 0.669199200 0.669199200 0.261215724 0.419464973 0.137553881
#> [79] 0.743108309 0.459491053 0.057521882 0.949219528 0.479305000 0.176826296
#> [85] 0.724694815 0.389920395 0.389920395 0.982985144 0.126777706 0.940466901
#> [91] 0.242329559 0.429458019 0.498761341 0.761371978 0.369730933 0.537251089
#> [97] 0.300412342 0.807075834 0.449463241 0.622037664 0.687907317 0.949219528
#> [103] 0.043156051 0.095239298 0.905195203 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 188 125 36 130 39 125.1 6 30 129 96 180 52 127
#> 16.16 15.65 21.19 16.47 15.59 15.65 15.64 17.43 23.41 14.54 14.82 10.42 3.53
#> 150 171 32 145 25 78 179 60 107 78.1 107.1 39.1 96.1
#> 20.33 16.57 20.90 10.07 6.32 23.88 18.63 13.15 11.18 23.88 11.18 15.59 14.54
#> 5 183 14 107.2 70 76 60.1 184 37 107.3 24 128 133
#> 16.43 9.24 12.89 11.18 7.38 19.22 13.15 17.77 12.52 11.18 23.89 20.35 14.65
#> 61 10 100 187 92 90 110 190 5.1 97 105 150.1 177
#> 10.12 10.53 16.07 9.92 22.92 20.94 17.56 20.81 16.43 19.14 19.75 20.33 12.53
#> 97.1 15 129.1 24.1 58 192 15.1 49 25.1 58.1 39.2 60.2 177.1
#> 19.14 22.68 23.41 23.89 19.34 16.44 22.68 12.19 6.32 19.34 15.59 13.15 12.53
#> 10.1 166 139 140 36.1 177.2 88 179.1 13 13.1 105.1 117 139.1
#> 10.53 19.98 21.49 12.68 21.19 12.53 18.37 18.63 14.34 14.34 19.75 17.46 21.49
#> 140.1 106 129.2 25.2 130.1 90.1 14.1 110.1 110.2 127.1 194 77 166.1
#> 12.68 16.67 23.41 6.32 16.47 20.94 12.89 17.56 17.56 3.53 22.40 7.27 19.98
#> 111 181 154 134 188.1 76.1 49.1 45 180.1 81 25.3 168 113
#> 17.45 16.46 12.63 17.81 16.16 19.22 12.19 17.42 14.82 14.06 6.32 23.72 22.86
#> 101 156 132 27 122 137 102 144 151 119 7 84 196
#> 9.97 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87 22 46 3 118 196.1 82 138 144.1 147 163 116 174
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9 19 137.1 27.1 137.2 20 144.2 118.1 186 9.1 152 71 46.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126 82.1 131 135 98 109 148 53 137.3 3.1 198 82.2 71.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95 9.2 174.1 53.1 131.1 11 19.1 103 34 11.1 31 178 103.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 38 2 9.3 67 102.1 174.2 67.1 200 198.1 47 132.1 174.3 135.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1 126.1 53.2 38.1 3.2 178.1 198.2 118.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[24]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.009803105 0.371987704 0.115743082
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.282046733 0.006825786 0.106189533
#> grade_iii, Cure model
#> 0.466637588
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 56 12.21 1 60 0 0
#> 60 13.15 1 38 1 0
#> 36 21.19 1 48 0 1
#> 57 14.46 1 45 0 1
#> 51 18.23 1 83 0 1
#> 6 15.64 1 39 0 0
#> 68 20.62 1 44 0 0
#> 76 19.22 1 54 0 1
#> 15 22.68 1 48 0 0
#> 199 19.81 1 NA 0 1
#> 129 23.41 1 53 1 0
#> 133 14.65 1 57 0 0
#> 183 9.24 1 67 1 0
#> 90 20.94 1 50 0 1
#> 129.1 23.41 1 53 1 0
#> 55 19.34 1 69 0 1
#> 14 12.89 1 21 0 0
#> 199.1 19.81 1 NA 0 1
#> 111 17.45 1 47 0 1
#> 6.1 15.64 1 39 0 0
#> 50 10.02 1 NA 1 0
#> 105 19.75 1 60 0 0
#> 164 23.60 1 76 0 1
#> 177 12.53 1 75 0 0
#> 93 10.33 1 52 0 1
#> 195 11.76 1 NA 1 0
#> 150 20.33 1 48 0 0
#> 39 15.59 1 37 0 1
#> 69 23.23 1 25 0 1
#> 128 20.35 1 35 0 1
#> 183.1 9.24 1 67 1 0
#> 29 15.45 1 68 1 0
#> 159 10.55 1 50 0 1
#> 150.1 20.33 1 48 0 0
#> 81 14.06 1 34 0 0
#> 60.1 13.15 1 38 1 0
#> 194 22.40 1 38 0 1
#> 45 17.42 1 54 0 1
#> 41 18.02 1 40 1 0
#> 52 10.42 1 52 0 1
#> 100 16.07 1 60 0 0
#> 188 16.16 1 46 0 1
#> 168 23.72 1 70 0 0
#> 180 14.82 1 37 0 0
#> 78 23.88 1 43 0 0
#> 145 10.07 1 65 1 0
#> 97 19.14 1 65 0 1
#> 43 12.10 1 61 0 1
#> 36.1 21.19 1 48 0 1
#> 36.2 21.19 1 48 0 1
#> 139 21.49 1 63 1 0
#> 10 10.53 1 34 0 0
#> 68.1 20.62 1 44 0 0
#> 61 10.12 1 36 0 1
#> 181 16.46 1 45 0 1
#> 125 15.65 1 67 1 0
#> 190 20.81 1 42 1 0
#> 52.1 10.42 1 52 0 1
#> 140 12.68 1 59 1 0
#> 133.1 14.65 1 57 0 0
#> 14.1 12.89 1 21 0 0
#> 25 6.32 1 34 1 0
#> 170 19.54 1 43 0 1
#> 6.2 15.64 1 39 0 0
#> 10.1 10.53 1 34 0 0
#> 32 20.90 1 37 1 0
#> 92 22.92 1 47 0 1
#> 36.3 21.19 1 48 0 1
#> 60.2 13.15 1 38 1 0
#> 5 16.43 1 51 0 1
#> 5.1 16.43 1 51 0 1
#> 52.2 10.42 1 52 0 1
#> 41.1 18.02 1 40 1 0
#> 184 17.77 1 38 0 0
#> 149 8.37 1 33 1 0
#> 197 21.60 1 69 1 0
#> 49 12.19 1 48 1 0
#> 70 7.38 1 30 1 0
#> 179 18.63 1 42 0 0
#> 10.2 10.53 1 34 0 0
#> 145.1 10.07 1 65 1 0
#> 190.1 20.81 1 42 1 0
#> 42 12.43 1 49 0 1
#> 130 16.47 1 53 0 1
#> 92.1 22.92 1 47 0 1
#> 29.1 15.45 1 68 1 0
#> 149.1 8.37 1 33 1 0
#> 96 14.54 1 33 0 1
#> 199.2 19.81 1 NA 0 1
#> 58 19.34 1 39 0 0
#> 157 15.10 1 47 0 0
#> 42.1 12.43 1 49 0 1
#> 24 23.89 1 38 0 0
#> 181.1 16.46 1 45 0 1
#> 10.3 10.53 1 34 0 0
#> 187 9.92 1 39 1 0
#> 66 22.13 1 53 0 0
#> 108 18.29 1 39 0 1
#> 157.1 15.10 1 47 0 0
#> 60.3 13.15 1 38 1 0
#> 149.2 8.37 1 33 1 0
#> 63 22.77 1 31 1 0
#> 175 21.91 1 43 0 0
#> 197.1 21.60 1 69 1 0
#> 190.2 20.81 1 42 1 0
#> 14.2 12.89 1 21 0 0
#> 90.1 20.94 1 50 0 1
#> 175.1 21.91 1 43 0 0
#> 107 11.18 1 54 1 0
#> 89 11.44 1 NA 0 0
#> 145.2 10.07 1 65 1 0
#> 197.2 21.60 1 69 1 0
#> 17 24.00 0 38 0 1
#> 74 24.00 0 43 0 1
#> 141 24.00 0 44 1 0
#> 73 24.00 0 NA 0 1
#> 152 24.00 0 36 0 1
#> 122 24.00 0 66 0 0
#> 131 24.00 0 66 0 0
#> 7 24.00 0 37 1 0
#> 87 24.00 0 27 0 0
#> 144 24.00 0 28 0 1
#> 122.1 24.00 0 66 0 0
#> 112 24.00 0 61 0 0
#> 48 24.00 0 31 1 0
#> 174 24.00 0 49 1 0
#> 27 24.00 0 63 1 0
#> 67 24.00 0 25 0 0
#> 144.1 24.00 0 28 0 1
#> 1 24.00 0 23 1 0
#> 152.1 24.00 0 36 0 1
#> 141.1 24.00 0 44 1 0
#> 191 24.00 0 60 0 1
#> 48.1 24.00 0 31 1 0
#> 83 24.00 0 6 0 0
#> 28 24.00 0 67 1 0
#> 109 24.00 0 48 0 0
#> 200 24.00 0 64 0 0
#> 112.1 24.00 0 61 0 0
#> 186 24.00 0 45 1 0
#> 95 24.00 0 68 0 1
#> 141.2 24.00 0 44 1 0
#> 33 24.00 0 53 0 0
#> 19 24.00 0 57 0 1
#> 34 24.00 0 36 0 0
#> 73.1 24.00 0 NA 0 1
#> 191.1 24.00 0 60 0 1
#> 196 24.00 0 19 0 0
#> 182 24.00 0 35 0 0
#> 160 24.00 0 31 1 0
#> 147 24.00 0 76 1 0
#> 27.1 24.00 0 63 1 0
#> 12 24.00 0 63 0 0
#> 103 24.00 0 56 1 0
#> 3 24.00 0 31 1 0
#> 185 24.00 0 44 1 0
#> 151 24.00 0 42 0 0
#> 137 24.00 0 45 1 0
#> 151.1 24.00 0 42 0 0
#> 83.1 24.00 0 6 0 0
#> 131.1 24.00 0 66 0 0
#> 17.1 24.00 0 38 0 1
#> 161 24.00 0 45 0 0
#> 143 24.00 0 51 0 0
#> 131.2 24.00 0 66 0 0
#> 74.1 24.00 0 43 0 1
#> 173 24.00 0 19 0 1
#> 165 24.00 0 47 0 0
#> 196.1 24.00 0 19 0 0
#> 162 24.00 0 51 0 0
#> 98 24.00 0 34 1 0
#> 160.1 24.00 0 31 1 0
#> 27.2 24.00 0 63 1 0
#> 1.1 24.00 0 23 1 0
#> 19.1 24.00 0 57 0 1
#> 28.1 24.00 0 67 1 0
#> 152.2 24.00 0 36 0 1
#> 64 24.00 0 43 0 0
#> 152.3 24.00 0 36 0 1
#> 17.2 24.00 0 38 0 1
#> 34.1 24.00 0 36 0 0
#> 116 24.00 0 58 0 1
#> 12.1 24.00 0 63 0 0
#> 126 24.00 0 48 0 0
#> 11 24.00 0 42 0 1
#> 173.1 24.00 0 19 0 1
#> 174.1 24.00 0 49 1 0
#> 147.1 24.00 0 76 1 0
#> 46 24.00 0 71 0 0
#> 138 24.00 0 44 1 0
#> 28.2 24.00 0 67 1 0
#> 94 24.00 0 51 0 1
#> 121 24.00 0 57 1 0
#> 84 24.00 0 39 0 1
#> 131.3 24.00 0 66 0 0
#> 21 24.00 0 47 0 0
#> 131.4 24.00 0 66 0 0
#> 73.2 24.00 0 NA 0 1
#> 27.3 24.00 0 63 1 0
#> 11.1 24.00 0 42 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.282 NA NA NA
#> 2 age, Cure model 0.00683 NA NA NA
#> 3 grade_ii, Cure model 0.106 NA NA NA
#> 4 grade_iii, Cure model 0.467 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00980 NA NA NA
#> 2 grade_ii, Survival model 0.372 NA NA NA
#> 3 grade_iii, Survival model 0.116 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.282047 0.006826 0.106190 0.466638
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 262.5
#> Residual Deviance: 260.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.282046733 0.006825786 0.106189533 0.466637588
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.009803105 0.371987704 0.115743082
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.6957070970 0.5721712529 0.1012741106 0.5496218459 0.2851942716
#> [6] 0.4213973990 0.1742655961 0.2488536318 0.0441168759 0.0141978721
#> [11] 0.5164017270 0.9127257691 0.1289103290 0.0141978721 0.2315407835
#> [16] 0.6160789562 0.3225119814 0.4213973990 0.2144667878 0.0093295392
#> [21] 0.6610754874 0.8384975375 0.1980978345 0.4522337378 0.0231051763
#> [26] 0.1899940245 0.9127257691 0.4628092703 0.7428811561 0.1980978345
#> [31] 0.5608644253 0.5721712529 0.0499159268 0.3320603553 0.2945696304
#> [36] 0.8021702049 0.4008719993 0.3907558655 0.0054314743 0.5054631350
#> [41] 0.0025824454 0.8632299863 0.2577731097 0.7191970400 0.1012741106
#> [46] 0.1012741106 0.0941814072 0.7547965757 0.1742655961 0.8508447863
#> [51] 0.3514362420 0.4111029452 0.1519046981 0.8021702049 0.6496494744
#> [56] 0.5164017270 0.6160789562 0.9874628570 0.2229607129 0.4213973990
#> [61] 0.7547965757 0.1441014754 0.0282368568 0.1012741106 0.5721712529
#> [66] 0.3709297759 0.3709297759 0.8021702049 0.2945696304 0.3130453995
#> [71] 0.9377329980 0.0747599417 0.7074429156 0.9749194351 0.2668198067
#> [76] 0.7547965757 0.8632299863 0.1519046981 0.6726052492 0.3417026654
#> [81] 0.0282368568 0.4628092703 0.9377329980 0.5384427871 0.2315407835
#> [86] 0.4839626814 0.6726052492 0.0006049268 0.3514362420 0.7547965757
#> [91] 0.9002208435 0.0558723048 0.2759712441 0.4839626814 0.5721712529
#> [96] 0.9377329980 0.0385910789 0.0620980212 0.0747599417 0.1519046981
#> [101] 0.6160789562 0.1289103290 0.0620980212 0.7310251289 0.8632299863
#> [106] 0.0747599417 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [191] 0.0000000000
#>
#> $Time
#> 56 60 36 57 51 6 68 76 15 129 133 183 90
#> 12.21 13.15 21.19 14.46 18.23 15.64 20.62 19.22 22.68 23.41 14.65 9.24 20.94
#> 129.1 55 14 111 6.1 105 164 177 93 150 39 69 128
#> 23.41 19.34 12.89 17.45 15.64 19.75 23.60 12.53 10.33 20.33 15.59 23.23 20.35
#> 183.1 29 159 150.1 81 60.1 194 45 41 52 100 188 168
#> 9.24 15.45 10.55 20.33 14.06 13.15 22.40 17.42 18.02 10.42 16.07 16.16 23.72
#> 180 78 145 97 43 36.1 36.2 139 10 68.1 61 181 125
#> 14.82 23.88 10.07 19.14 12.10 21.19 21.19 21.49 10.53 20.62 10.12 16.46 15.65
#> 190 52.1 140 133.1 14.1 25 170 6.2 10.1 32 92 36.3 60.2
#> 20.81 10.42 12.68 14.65 12.89 6.32 19.54 15.64 10.53 20.90 22.92 21.19 13.15
#> 5 5.1 52.2 41.1 184 149 197 49 70 179 10.2 145.1 190.1
#> 16.43 16.43 10.42 18.02 17.77 8.37 21.60 12.19 7.38 18.63 10.53 10.07 20.81
#> 42 130 92.1 29.1 149.1 96 58 157 42.1 24 181.1 10.3 187
#> 12.43 16.47 22.92 15.45 8.37 14.54 19.34 15.10 12.43 23.89 16.46 10.53 9.92
#> 66 108 157.1 60.3 149.2 63 175 197.1 190.2 14.2 90.1 175.1 107
#> 22.13 18.29 15.10 13.15 8.37 22.77 21.91 21.60 20.81 12.89 20.94 21.91 11.18
#> 145.2 197.2 17 74 141 152 122 131 7 87 144 122.1 112
#> 10.07 21.60 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 48 174 27 67 144.1 1 152.1 141.1 191 48.1 83 28 109
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 200 112.1 186 95 141.2 33 19 34 191.1 196 182 160 147
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 27.1 12 103 3 185 151 137 151.1 83.1 131.1 17.1 161 143
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131.2 74.1 173 165 196.1 162 98 160.1 27.2 1.1 19.1 28.1 152.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64 152.3 17.2 34.1 116 12.1 126 11 173.1 174.1 147.1 46 138
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28.2 94 121 84 131.3 21 131.4 27.3 11.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[25]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01874807 0.43657308 0.20002765
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.9410785 0.0149115 0.2790045
#> grade_iii, Cure model
#> 0.9355315
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 128 20.35 1 35 0 1
#> 41 18.02 1 40 1 0
#> 105 19.75 1 60 0 0
#> 140 12.68 1 59 1 0
#> 86 23.81 1 58 0 1
#> 150 20.33 1 48 0 0
#> 4 17.64 1 NA 0 1
#> 129 23.41 1 53 1 0
#> 128.1 20.35 1 35 0 1
#> 81 14.06 1 34 0 0
#> 111 17.45 1 47 0 1
#> 49 12.19 1 48 1 0
#> 150.1 20.33 1 48 0 0
#> 134 17.81 1 47 1 0
#> 157 15.10 1 47 0 0
#> 197 21.60 1 69 1 0
#> 40 18.00 1 28 1 0
#> 36 21.19 1 48 0 1
#> 197.1 21.60 1 69 1 0
#> 134.1 17.81 1 47 1 0
#> 91 5.33 1 61 0 1
#> 70 7.38 1 30 1 0
#> 18 15.21 1 49 1 0
#> 68 20.62 1 44 0 0
#> 85 16.44 1 36 0 0
#> 188 16.16 1 46 0 1
#> 195 11.76 1 NA 1 0
#> 153 21.33 1 55 1 0
#> 76 19.22 1 54 0 1
#> 8 18.43 1 32 0 0
#> 183 9.24 1 67 1 0
#> 164 23.60 1 76 0 1
#> 70.1 7.38 1 30 1 0
#> 26 15.77 1 49 0 1
#> 97 19.14 1 65 0 1
#> 86.1 23.81 1 58 0 1
#> 59 10.16 1 NA 1 0
#> 171 16.57 1 41 0 1
#> 93 10.33 1 52 0 1
#> 155 13.08 1 26 0 0
#> 24 23.89 1 38 0 0
#> 39 15.59 1 37 0 1
#> 117 17.46 1 26 0 1
#> 101 9.97 1 10 0 1
#> 154 12.63 1 20 1 0
#> 24.1 23.89 1 38 0 0
#> 175 21.91 1 43 0 0
#> 92 22.92 1 47 0 1
#> 195.1 11.76 1 NA 1 0
#> 127 3.53 1 62 0 1
#> 14 12.89 1 21 0 0
#> 106 16.67 1 49 1 0
#> 86.2 23.81 1 58 0 1
#> 192 16.44 1 31 1 0
#> 49.1 12.19 1 48 1 0
#> 92.1 22.92 1 47 0 1
#> 61 10.12 1 36 0 1
#> 5 16.43 1 51 0 1
#> 108 18.29 1 39 0 1
#> 26.1 15.77 1 49 0 1
#> 105.1 19.75 1 60 0 0
#> 177 12.53 1 75 0 0
#> 50 10.02 1 NA 1 0
#> 125 15.65 1 67 1 0
#> 192.1 16.44 1 31 1 0
#> 93.1 10.33 1 52 0 1
#> 145 10.07 1 65 1 0
#> 189 10.51 1 NA 1 0
#> 100 16.07 1 60 0 0
#> 4.1 17.64 1 NA 0 1
#> 199 19.81 1 NA 0 1
#> 197.2 21.60 1 69 1 0
#> 10 10.53 1 34 0 0
#> 129.1 23.41 1 53 1 0
#> 179 18.63 1 42 0 0
#> 195.2 11.76 1 NA 1 0
#> 59.1 10.16 1 NA 1 0
#> 10.1 10.53 1 34 0 0
#> 90 20.94 1 50 0 1
#> 13 14.34 1 54 0 1
#> 179.1 18.63 1 42 0 0
#> 96 14.54 1 33 0 1
#> 63 22.77 1 31 1 0
#> 181 16.46 1 45 0 1
#> 96.1 14.54 1 33 0 1
#> 150.2 20.33 1 48 0 0
#> 194 22.40 1 38 0 1
#> 114 13.68 1 NA 0 0
#> 91.1 5.33 1 61 0 1
#> 39.1 15.59 1 37 0 1
#> 58 19.34 1 39 0 0
#> 195.3 11.76 1 NA 1 0
#> 26.2 15.77 1 49 0 1
#> 99 21.19 1 38 0 1
#> 79 16.23 1 54 1 0
#> 90.1 20.94 1 50 0 1
#> 124 9.73 1 NA 1 0
#> 5.1 16.43 1 51 0 1
#> 179.2 18.63 1 42 0 0
#> 136 21.83 1 43 0 1
#> 39.2 15.59 1 37 0 1
#> 167 15.55 1 56 1 0
#> 50.1 10.02 1 NA 1 0
#> 154.1 12.63 1 20 1 0
#> 117.1 17.46 1 26 0 1
#> 18.1 15.21 1 49 1 0
#> 166 19.98 1 48 0 0
#> 111.1 17.45 1 47 0 1
#> 133 14.65 1 57 0 0
#> 97.1 19.14 1 65 0 1
#> 159 10.55 1 50 0 1
#> 181.1 16.46 1 45 0 1
#> 141 24.00 0 44 1 0
#> 31 24.00 0 36 0 1
#> 176 24.00 0 43 0 1
#> 193 24.00 0 45 0 1
#> 31.1 24.00 0 36 0 1
#> 173 24.00 0 19 0 1
#> 176.1 24.00 0 43 0 1
#> 19 24.00 0 57 0 1
#> 182 24.00 0 35 0 0
#> 112 24.00 0 61 0 0
#> 82 24.00 0 34 0 0
#> 73 24.00 0 NA 0 1
#> 44 24.00 0 56 0 0
#> 62 24.00 0 71 0 0
#> 196 24.00 0 19 0 0
#> 35 24.00 0 51 0 0
#> 109 24.00 0 48 0 0
#> 196.1 24.00 0 19 0 0
#> 74 24.00 0 43 0 1
#> 160 24.00 0 31 1 0
#> 137 24.00 0 45 1 0
#> 185 24.00 0 44 1 0
#> 165 24.00 0 47 0 0
#> 72 24.00 0 40 0 1
#> 186 24.00 0 45 1 0
#> 73.1 24.00 0 NA 0 1
#> 151 24.00 0 42 0 0
#> 48 24.00 0 31 1 0
#> 75 24.00 0 21 1 0
#> 176.2 24.00 0 43 0 1
#> 162 24.00 0 51 0 0
#> 65 24.00 0 57 1 0
#> 104 24.00 0 50 1 0
#> 73.2 24.00 0 NA 0 1
#> 19.1 24.00 0 57 0 1
#> 11 24.00 0 42 0 1
#> 19.2 24.00 0 57 0 1
#> 193.1 24.00 0 45 0 1
#> 72.1 24.00 0 40 0 1
#> 71 24.00 0 51 0 0
#> 165.1 24.00 0 47 0 0
#> 48.1 24.00 0 31 1 0
#> 33 24.00 0 53 0 0
#> 152 24.00 0 36 0 1
#> 102 24.00 0 49 0 0
#> 46 24.00 0 71 0 0
#> 196.2 24.00 0 19 0 0
#> 74.1 24.00 0 43 0 1
#> 75.1 24.00 0 21 1 0
#> 84 24.00 0 39 0 1
#> 82.1 24.00 0 34 0 0
#> 80 24.00 0 41 0 0
#> 1 24.00 0 23 1 0
#> 75.2 24.00 0 21 1 0
#> 148 24.00 0 61 1 0
#> 126 24.00 0 48 0 0
#> 186.1 24.00 0 45 1 0
#> 137.1 24.00 0 45 1 0
#> 28 24.00 0 67 1 0
#> 7 24.00 0 37 1 0
#> 82.2 24.00 0 34 0 0
#> 196.3 24.00 0 19 0 0
#> 95 24.00 0 68 0 1
#> 94 24.00 0 51 0 1
#> 165.2 24.00 0 47 0 0
#> 48.2 24.00 0 31 1 0
#> 9 24.00 0 31 1 0
#> 47 24.00 0 38 0 1
#> 162.1 24.00 0 51 0 0
#> 182.1 24.00 0 35 0 0
#> 71.1 24.00 0 51 0 0
#> 160.1 24.00 0 31 1 0
#> 144 24.00 0 28 0 1
#> 65.1 24.00 0 57 1 0
#> 160.2 24.00 0 31 1 0
#> 186.2 24.00 0 45 1 0
#> 163 24.00 0 66 0 0
#> 98 24.00 0 34 1 0
#> 151.1 24.00 0 42 0 0
#> 33.1 24.00 0 53 0 0
#> 28.1 24.00 0 67 1 0
#> 147 24.00 0 76 1 0
#> 3 24.00 0 31 1 0
#> 182.2 24.00 0 35 0 0
#> 95.1 24.00 0 68 0 1
#> 33.2 24.00 0 53 0 0
#> 151.2 24.00 0 42 0 0
#> 115 24.00 0 NA 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.941 NA NA NA
#> 2 age, Cure model 0.0149 NA NA NA
#> 3 grade_ii, Cure model 0.279 NA NA NA
#> 4 grade_iii, Cure model 0.936 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0187 NA NA NA
#> 2 grade_ii, Survival model 0.437 NA NA NA
#> 3 grade_iii, Survival model 0.200 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.94108 0.01491 0.27900 0.93553
#>
#> Degrees of Freedom: 181 Total (i.e. Null); 178 Residual
#> Null Deviance: 251.2
#> Residual Deviance: 242.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.9410785 0.0149115 0.2790045 0.9355315
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01874807 0.43657308 0.20002765
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.0618265440 0.1851299914 0.0962445008 0.6580820134 0.0008379244
#> [6] 0.0723648994 0.0048321971 0.0618265440 0.6111790069 0.2434887092
#> [11] 0.7216459602 0.0723648994 0.2042874529 0.5366518116 0.0242164782
#> [16] 0.1946887483 0.0387071805 0.0242164782 0.2042874529 0.9450045641
#> [21] 0.9094360023 0.5083392331 0.0566515857 0.3078413552 0.3770177484
#> [26] 0.0346148946 0.1173356433 0.1664785369 0.8915579560 0.0032442522
#> [31] 0.9094360023 0.4019553334 0.1249481191 0.0008379244 0.2748308934
#> [36] 0.8043617585 0.6266722053 0.0001090705 0.4538185488 0.2236731593
#> [41] 0.8738782248 0.6740359821 0.0001090705 0.0180774058 0.0083510879
#> [46] 0.9814101088 0.6423146187 0.2641346973 0.0008379244 0.3078413552
#> [51] 0.7216459602 0.0083510879 0.8387057275 0.3413342616 0.1757022589
#> [56] 0.4019553334 0.0962445008 0.7054731304 0.4403899065 0.3078413552
#> [61] 0.8043617585 0.8561939887 0.3893517232 0.0242164782 0.7707908217
#> [66] 0.0048321971 0.1409153166 0.7707908217 0.0472347510 0.5958687563
#> [71] 0.1409153166 0.5660620753 0.0128181244 0.2857107672 0.5660620753
#> [76] 0.0723648994 0.0153572741 0.9450045641 0.4538185488 0.1099883631
#> [81] 0.4019553334 0.0387071805 0.3648761899 0.0472347510 0.3413342616
#> [86] 0.1409153166 0.0210450852 0.4538185488 0.4942840496 0.6740359821
#> [91] 0.2236731593 0.5083392331 0.0897588670 0.2434887092 0.5512281755
#> [96] 0.1249481191 0.7541637368 0.2857107672 0.0000000000 0.0000000000
#> [101] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000
#>
#> $Time
#> 128 41 105 140 86 150 129 128.1 81 111 49 150.1 134
#> 20.35 18.02 19.75 12.68 23.81 20.33 23.41 20.35 14.06 17.45 12.19 20.33 17.81
#> 157 197 40 36 197.1 134.1 91 70 18 68 85 188 153
#> 15.10 21.60 18.00 21.19 21.60 17.81 5.33 7.38 15.21 20.62 16.44 16.16 21.33
#> 76 8 183 164 70.1 26 97 86.1 171 93 155 24 39
#> 19.22 18.43 9.24 23.60 7.38 15.77 19.14 23.81 16.57 10.33 13.08 23.89 15.59
#> 117 101 154 24.1 175 92 127 14 106 86.2 192 49.1 92.1
#> 17.46 9.97 12.63 23.89 21.91 22.92 3.53 12.89 16.67 23.81 16.44 12.19 22.92
#> 61 5 108 26.1 105.1 177 125 192.1 93.1 145 100 197.2 10
#> 10.12 16.43 18.29 15.77 19.75 12.53 15.65 16.44 10.33 10.07 16.07 21.60 10.53
#> 129.1 179 10.1 90 13 179.1 96 63 181 96.1 150.2 194 91.1
#> 23.41 18.63 10.53 20.94 14.34 18.63 14.54 22.77 16.46 14.54 20.33 22.40 5.33
#> 39.1 58 26.2 99 79 90.1 5.1 179.2 136 39.2 167 154.1 117.1
#> 15.59 19.34 15.77 21.19 16.23 20.94 16.43 18.63 21.83 15.59 15.55 12.63 17.46
#> 18.1 166 111.1 133 97.1 159 181.1 141 31 176 193 31.1 173
#> 15.21 19.98 17.45 14.65 19.14 10.55 16.46 24.00 24.00 24.00 24.00 24.00 24.00
#> 176.1 19 182 112 82 44 62 196 35 109 196.1 74 160
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137 185 165 72 186 151 48 75 176.2 162 65 104 19.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 11 19.2 193.1 72.1 71 165.1 48.1 33 152 102 46 196.2 74.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75.1 84 82.1 80 1 75.2 148 126 186.1 137.1 28 7 82.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 196.3 95 94 165.2 48.2 9 47 162.1 182.1 71.1 160.1 144 65.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 160.2 186.2 163 98 151.1 33.1 28.1 147 3 182.2 95.1 33.2 151.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[26]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.003719209 0.324915736 0.308292318
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.53822917 0.00648764 0.18919734
#> grade_iii, Cure model
#> 1.16017003
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 171 16.57 1 41 0 1
#> 130 16.47 1 53 0 1
#> 77 7.27 1 67 0 1
#> 52 10.42 1 52 0 1
#> 197 21.60 1 69 1 0
#> 99 21.19 1 38 0 1
#> 100 16.07 1 60 0 0
#> 92 22.92 1 47 0 1
#> 149 8.37 1 33 1 0
#> 175 21.91 1 43 0 0
#> 78 23.88 1 43 0 0
#> 24 23.89 1 38 0 0
#> 194 22.40 1 38 0 1
#> 197.1 21.60 1 69 1 0
#> 18 15.21 1 49 1 0
#> 56 12.21 1 60 0 0
#> 167 15.55 1 56 1 0
#> 32 20.90 1 37 1 0
#> 14 12.89 1 21 0 0
#> 32.1 20.90 1 37 1 0
#> 59 10.16 1 NA 1 0
#> 108 18.29 1 39 0 1
#> 86 23.81 1 58 0 1
#> 85 16.44 1 36 0 0
#> 4 17.64 1 NA 0 1
#> 130.1 16.47 1 53 0 1
#> 51 18.23 1 83 0 1
#> 96 14.54 1 33 0 1
#> 29 15.45 1 68 1 0
#> 85.1 16.44 1 36 0 0
#> 93 10.33 1 52 0 1
#> 41 18.02 1 40 1 0
#> 15 22.68 1 48 0 0
#> 136 21.83 1 43 0 1
#> 184 17.77 1 38 0 0
#> 50 10.02 1 NA 1 0
#> 77.1 7.27 1 67 0 1
#> 189 10.51 1 NA 1 0
#> 179 18.63 1 42 0 0
#> 177 12.53 1 75 0 0
#> 66 22.13 1 53 0 0
#> 66.1 22.13 1 53 0 0
#> 101 9.97 1 10 0 1
#> 154 12.63 1 20 1 0
#> 89 11.44 1 NA 0 0
#> 155 13.08 1 26 0 0
#> 91 5.33 1 61 0 1
#> 70 7.38 1 30 1 0
#> 153 21.33 1 55 1 0
#> 180 14.82 1 37 0 0
#> 89.1 11.44 1 NA 0 0
#> 52.1 10.42 1 52 0 1
#> 86.1 23.81 1 58 0 1
#> 70.1 7.38 1 30 1 0
#> 145 10.07 1 65 1 0
#> 157 15.10 1 47 0 0
#> 169 22.41 1 46 0 0
#> 36 21.19 1 48 0 1
#> 51.1 18.23 1 83 0 1
#> 189.1 10.51 1 NA 1 0
#> 77.2 7.27 1 67 0 1
#> 91.1 5.33 1 61 0 1
#> 39 15.59 1 37 0 1
#> 59.1 10.16 1 NA 1 0
#> 166 19.98 1 48 0 0
#> 155.1 13.08 1 26 0 0
#> 6 15.64 1 39 0 0
#> 192 16.44 1 31 1 0
#> 113 22.86 1 34 0 0
#> 10 10.53 1 34 0 0
#> 179.1 18.63 1 42 0 0
#> 18.1 15.21 1 49 1 0
#> 189.2 10.51 1 NA 1 0
#> 29.1 15.45 1 68 1 0
#> 36.1 21.19 1 48 0 1
#> 81 14.06 1 34 0 0
#> 49 12.19 1 48 1 0
#> 127 3.53 1 62 0 1
#> 127.1 3.53 1 62 0 1
#> 68 20.62 1 44 0 0
#> 125 15.65 1 67 1 0
#> 77.3 7.27 1 67 0 1
#> 99.1 21.19 1 38 0 1
#> 188 16.16 1 46 0 1
#> 63 22.77 1 31 1 0
#> 164 23.60 1 76 0 1
#> 171.1 16.57 1 41 0 1
#> 129 23.41 1 53 1 0
#> 128 20.35 1 35 0 1
#> 124 9.73 1 NA 1 0
#> 60 13.15 1 38 1 0
#> 149.1 8.37 1 33 1 0
#> 45 17.42 1 54 0 1
#> 197.2 21.60 1 69 1 0
#> 153.1 21.33 1 55 1 0
#> 107 11.18 1 54 1 0
#> 171.2 16.57 1 41 0 1
#> 117 17.46 1 26 0 1
#> 13 14.34 1 54 0 1
#> 153.2 21.33 1 55 1 0
#> 88 18.37 1 47 0 0
#> 77.4 7.27 1 67 0 1
#> 55 19.34 1 69 0 1
#> 5 16.43 1 51 0 1
#> 167.1 15.55 1 56 1 0
#> 99.2 21.19 1 38 0 1
#> 125.1 15.65 1 67 1 0
#> 18.2 15.21 1 49 1 0
#> 6.1 15.64 1 39 0 0
#> 195 11.76 1 NA 1 0
#> 197.3 21.60 1 69 1 0
#> 63.1 22.77 1 31 1 0
#> 72 24.00 0 40 0 1
#> 17 24.00 0 38 0 1
#> 193 24.00 0 45 0 1
#> 65 24.00 0 57 1 0
#> 21 24.00 0 47 0 0
#> 163 24.00 0 66 0 0
#> 27 24.00 0 63 1 0
#> 126 24.00 0 48 0 0
#> 103 24.00 0 56 1 0
#> 186 24.00 0 45 1 0
#> 148 24.00 0 61 1 0
#> 73 24.00 0 NA 0 1
#> 9 24.00 0 31 1 0
#> 162 24.00 0 51 0 0
#> 138 24.00 0 44 1 0
#> 186.1 24.00 0 45 1 0
#> 116 24.00 0 58 0 1
#> 11 24.00 0 42 0 1
#> 9.1 24.00 0 31 1 0
#> 27.1 24.00 0 63 1 0
#> 83 24.00 0 6 0 0
#> 65.1 24.00 0 57 1 0
#> 138.1 24.00 0 44 1 0
#> 27.2 24.00 0 63 1 0
#> 120 24.00 0 68 0 1
#> 172 24.00 0 41 0 0
#> 112 24.00 0 61 0 0
#> 12 24.00 0 63 0 0
#> 200 24.00 0 64 0 0
#> 116.1 24.00 0 58 0 1
#> 151 24.00 0 42 0 0
#> 137 24.00 0 45 1 0
#> 72.1 24.00 0 40 0 1
#> 186.2 24.00 0 45 1 0
#> 46 24.00 0 71 0 0
#> 146 24.00 0 63 1 0
#> 102 24.00 0 49 0 0
#> 38 24.00 0 31 1 0
#> 160 24.00 0 31 1 0
#> 47 24.00 0 38 0 1
#> 146.1 24.00 0 63 1 0
#> 17.1 24.00 0 38 0 1
#> 35 24.00 0 51 0 0
#> 80 24.00 0 41 0 0
#> 193.1 24.00 0 45 0 1
#> 34 24.00 0 36 0 0
#> 165 24.00 0 47 0 0
#> 83.1 24.00 0 6 0 0
#> 178 24.00 0 52 1 0
#> 160.1 24.00 0 31 1 0
#> 104 24.00 0 50 1 0
#> 115 24.00 0 NA 1 0
#> 73.1 24.00 0 NA 0 1
#> 174 24.00 0 49 1 0
#> 53 24.00 0 32 0 1
#> 109 24.00 0 48 0 0
#> 17.2 24.00 0 38 0 1
#> 172.1 24.00 0 41 0 0
#> 44 24.00 0 56 0 0
#> 17.3 24.00 0 38 0 1
#> 80.1 24.00 0 41 0 0
#> 83.2 24.00 0 6 0 0
#> 11.1 24.00 0 42 0 1
#> 35.1 24.00 0 51 0 0
#> 143 24.00 0 51 0 0
#> 7 24.00 0 37 1 0
#> 176 24.00 0 43 0 1
#> 165.1 24.00 0 47 0 0
#> 146.2 24.00 0 63 1 0
#> 119 24.00 0 17 0 0
#> 200.1 24.00 0 64 0 0
#> 9.2 24.00 0 31 1 0
#> 109.1 24.00 0 48 0 0
#> 132 24.00 0 55 0 0
#> 21.1 24.00 0 47 0 0
#> 121 24.00 0 57 1 0
#> 80.2 24.00 0 41 0 0
#> 27.3 24.00 0 63 1 0
#> 98 24.00 0 34 1 0
#> 151.1 24.00 0 42 0 0
#> 21.2 24.00 0 47 0 0
#> 122 24.00 0 66 0 0
#> 182 24.00 0 35 0 0
#> 22 24.00 0 52 1 0
#> 65.2 24.00 0 57 1 0
#> 64 24.00 0 43 0 0
#> 7.1 24.00 0 37 1 0
#> 103.1 24.00 0 56 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.538 NA NA NA
#> 2 age, Cure model 0.00649 NA NA NA
#> 3 grade_ii, Cure model 0.189 NA NA NA
#> 4 grade_iii, Cure model 1.16 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00372 NA NA NA
#> 2 grade_ii, Survival model 0.325 NA NA NA
#> 3 grade_iii, Survival model 0.308 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.538229 0.006488 0.189197 1.160170
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 256.5
#> Residual Deviance: 245.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.53822917 0.00648764 0.18919734 1.16017003
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.003719209 0.324915736 0.308292318
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.469276295 0.497964127 0.917138911 0.832319680 0.194156526 0.264304882
#> [7] 0.565096633 0.075155946 0.879739556 0.171970130 0.017468482 0.005521191
#> [13] 0.139789637 0.194156526 0.661026185 0.794107755 0.622843154 0.311268660
#> [19] 0.765488171 0.311268660 0.400008699 0.031238619 0.517190267 0.497964127
#> [25] 0.409972448 0.708368956 0.641955844 0.517190267 0.851259409 0.429658355
#> [31] 0.118012523 0.183116948 0.439572466 0.917138911 0.370321660 0.784560229
#> [37] 0.150597298 0.150597298 0.870270668 0.775040901 0.746519597 0.962924423
#> [43] 0.898485500 0.234132109 0.698795423 0.832319680 0.031238619 0.898485500
#> [49] 0.860769590 0.689238724 0.128828494 0.264304882 0.409972448 0.917138911
#> [55] 0.962924423 0.613175387 0.350513953 0.746519597 0.593936282 0.517190267
#> [61] 0.086321519 0.822768717 0.370321660 0.661026185 0.641955844 0.264304882
#> [67] 0.727449031 0.803678297 0.981476351 0.981476351 0.330727083 0.574781002
#> [73] 0.917138911 0.264304882 0.555445348 0.097663192 0.052069957 0.469276295
#> [79] 0.063752097 0.340648516 0.736996743 0.879739556 0.459408266 0.194156526
#> [85] 0.234132109 0.813230906 0.469276295 0.449516143 0.717916183 0.234132109
#> [91] 0.390000760 0.917138911 0.360425013 0.545769342 0.622843154 0.264304882
#> [97] 0.574781002 0.661026185 0.593936282 0.194156526 0.097663192 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 171 130 77 52 197 99 100 92 149 175 78 24 194
#> 16.57 16.47 7.27 10.42 21.60 21.19 16.07 22.92 8.37 21.91 23.88 23.89 22.40
#> 197.1 18 56 167 32 14 32.1 108 86 85 130.1 51 96
#> 21.60 15.21 12.21 15.55 20.90 12.89 20.90 18.29 23.81 16.44 16.47 18.23 14.54
#> 29 85.1 93 41 15 136 184 77.1 179 177 66 66.1 101
#> 15.45 16.44 10.33 18.02 22.68 21.83 17.77 7.27 18.63 12.53 22.13 22.13 9.97
#> 154 155 91 70 153 180 52.1 86.1 70.1 145 157 169 36
#> 12.63 13.08 5.33 7.38 21.33 14.82 10.42 23.81 7.38 10.07 15.10 22.41 21.19
#> 51.1 77.2 91.1 39 166 155.1 6 192 113 10 179.1 18.1 29.1
#> 18.23 7.27 5.33 15.59 19.98 13.08 15.64 16.44 22.86 10.53 18.63 15.21 15.45
#> 36.1 81 49 127 127.1 68 125 77.3 99.1 188 63 164 171.1
#> 21.19 14.06 12.19 3.53 3.53 20.62 15.65 7.27 21.19 16.16 22.77 23.60 16.57
#> 129 128 60 149.1 45 197.2 153.1 107 171.2 117 13 153.2 88
#> 23.41 20.35 13.15 8.37 17.42 21.60 21.33 11.18 16.57 17.46 14.34 21.33 18.37
#> 77.4 55 5 167.1 99.2 125.1 18.2 6.1 197.3 63.1 72 17 193
#> 7.27 19.34 16.43 15.55 21.19 15.65 15.21 15.64 21.60 22.77 24.00 24.00 24.00
#> 65 21 163 27 126 103 186 148 9 162 138 186.1 116
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 11 9.1 27.1 83 65.1 138.1 27.2 120 172 112 12 200 116.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 151 137 72.1 186.2 46 146 102 38 160 47 146.1 17.1 35
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80 193.1 34 165 83.1 178 160.1 104 174 53 109 17.2 172.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44 17.3 80.1 83.2 11.1 35.1 143 7 176 165.1 146.2 119 200.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9.2 109.1 132 21.1 121 80.2 27.3 98 151.1 21.2 122 182 22
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 65.2 64 7.1 103.1
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[27]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.009115672 0.305002683 0.610553684
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.546962394 0.009141198 0.469421496
#> grade_iii, Cure model
#> 0.667344960
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 69 23.23 1 25 0 1
#> 63 22.77 1 31 1 0
#> 6 15.64 1 39 0 0
#> 180 14.82 1 37 0 0
#> 57 14.46 1 45 0 1
#> 66 22.13 1 53 0 0
#> 77 7.27 1 67 0 1
#> 43 12.10 1 61 0 1
#> 58 19.34 1 39 0 0
#> 190 20.81 1 42 1 0
#> 25 6.32 1 34 1 0
#> 167 15.55 1 56 1 0
#> 25.1 6.32 1 34 1 0
#> 52 10.42 1 52 0 1
#> 56 12.21 1 60 0 0
#> 140 12.68 1 59 1 0
#> 183 9.24 1 67 1 0
#> 192 16.44 1 31 1 0
#> 32 20.90 1 37 1 0
#> 15 22.68 1 48 0 0
#> 157 15.10 1 47 0 0
#> 189 10.51 1 NA 1 0
#> 140.1 12.68 1 59 1 0
#> 23 16.92 1 61 0 0
#> 166 19.98 1 48 0 0
#> 76 19.22 1 54 0 1
#> 81 14.06 1 34 0 0
#> 106 16.67 1 49 1 0
#> 195 11.76 1 NA 1 0
#> 89 11.44 1 NA 0 0
#> 66.1 22.13 1 53 0 0
#> 130 16.47 1 53 0 1
#> 58.1 19.34 1 39 0 0
#> 5 16.43 1 51 0 1
#> 150 20.33 1 48 0 0
#> 26 15.77 1 49 0 1
#> 168 23.72 1 70 0 0
#> 106.1 16.67 1 49 1 0
#> 150.1 20.33 1 48 0 0
#> 117 17.46 1 26 0 1
#> 30 17.43 1 78 0 0
#> 56.1 12.21 1 60 0 0
#> 111 17.45 1 47 0 1
#> 159 10.55 1 50 0 1
#> 107 11.18 1 54 1 0
#> 184 17.77 1 38 0 0
#> 125 15.65 1 67 1 0
#> 61 10.12 1 36 0 1
#> 171 16.57 1 41 0 1
#> 68 20.62 1 44 0 0
#> 32.1 20.90 1 37 1 0
#> 58.2 19.34 1 39 0 0
#> 145 10.07 1 65 1 0
#> 153 21.33 1 55 1 0
#> 8 18.43 1 32 0 0
#> 157.1 15.10 1 47 0 0
#> 179 18.63 1 42 0 0
#> 81.1 14.06 1 34 0 0
#> 192.1 16.44 1 31 1 0
#> 149 8.37 1 33 1 0
#> 194 22.40 1 38 0 1
#> 40 18.00 1 28 1 0
#> 153.1 21.33 1 55 1 0
#> 25.2 6.32 1 34 1 0
#> 93 10.33 1 52 0 1
#> 6.1 15.64 1 39 0 0
#> 190.1 20.81 1 42 1 0
#> 184.1 17.77 1 38 0 0
#> 76.1 19.22 1 54 0 1
#> 106.2 16.67 1 49 1 0
#> 187 9.92 1 39 1 0
#> 177 12.53 1 75 0 0
#> 139 21.49 1 63 1 0
#> 188 16.16 1 46 0 1
#> 89.1 11.44 1 NA 0 0
#> 136 21.83 1 43 0 1
#> 155 13.08 1 26 0 0
#> 57.1 14.46 1 45 0 1
#> 175 21.91 1 43 0 0
#> 197 21.60 1 69 1 0
#> 32.2 20.90 1 37 1 0
#> 177.1 12.53 1 75 0 0
#> 99 21.19 1 38 0 1
#> 127 3.53 1 62 0 1
#> 68.1 20.62 1 44 0 0
#> 60 13.15 1 38 1 0
#> 40.1 18.00 1 28 1 0
#> 129 23.41 1 53 1 0
#> 130.1 16.47 1 53 0 1
#> 154 12.63 1 20 1 0
#> 181 16.46 1 45 0 1
#> 106.3 16.67 1 49 1 0
#> 101 9.97 1 10 0 1
#> 108 18.29 1 39 0 1
#> 108.1 18.29 1 39 0 1
#> 88 18.37 1 47 0 0
#> 105 19.75 1 60 0 0
#> 66.2 22.13 1 53 0 0
#> 101.1 9.97 1 10 0 1
#> 125.1 15.65 1 67 1 0
#> 111.1 17.45 1 47 0 1
#> 145.1 10.07 1 65 1 0
#> 96 14.54 1 33 0 1
#> 15.1 22.68 1 48 0 0
#> 77.1 7.27 1 67 0 1
#> 37 12.52 1 57 1 0
#> 175.1 21.91 1 43 0 0
#> 63.1 22.77 1 31 1 0
#> 32.3 20.90 1 37 1 0
#> 199 19.81 1 NA 0 1
#> 130.2 16.47 1 53 0 1
#> 183.1 9.24 1 67 1 0
#> 11 24.00 0 42 0 1
#> 126 24.00 0 48 0 0
#> 80 24.00 0 41 0 0
#> 12 24.00 0 63 0 0
#> 75 24.00 0 21 1 0
#> 185 24.00 0 44 1 0
#> 44 24.00 0 56 0 0
#> 74 24.00 0 43 0 1
#> 118 24.00 0 44 1 0
#> 46 24.00 0 71 0 0
#> 34 24.00 0 36 0 0
#> 173 24.00 0 19 0 1
#> 71 24.00 0 51 0 0
#> 146 24.00 0 63 1 0
#> 161 24.00 0 45 0 0
#> 141 24.00 0 44 1 0
#> 132 24.00 0 55 0 0
#> 47 24.00 0 38 0 1
#> 152 24.00 0 36 0 1
#> 64 24.00 0 43 0 0
#> 135 24.00 0 58 1 0
#> 83 24.00 0 6 0 0
#> 142 24.00 0 53 0 0
#> 83.1 24.00 0 6 0 0
#> 102 24.00 0 49 0 0
#> 94 24.00 0 51 0 1
#> 80.1 24.00 0 41 0 0
#> 33 24.00 0 53 0 0
#> 12.1 24.00 0 63 0 0
#> 87 24.00 0 27 0 0
#> 162 24.00 0 51 0 0
#> 142.1 24.00 0 53 0 0
#> 118.1 24.00 0 44 1 0
#> 1 24.00 0 23 1 0
#> 165 24.00 0 47 0 0
#> 48 24.00 0 31 1 0
#> 141.1 24.00 0 44 1 0
#> 21 24.00 0 47 0 0
#> 94.1 24.00 0 51 0 1
#> 109 24.00 0 48 0 0
#> 115 24.00 0 NA 1 0
#> 1.1 24.00 0 23 1 0
#> 138 24.00 0 44 1 0
#> 191 24.00 0 60 0 1
#> 122 24.00 0 66 0 0
#> 152.1 24.00 0 36 0 1
#> 74.1 24.00 0 43 0 1
#> 12.2 24.00 0 63 0 0
#> 75.1 24.00 0 21 1 0
#> 122.1 24.00 0 66 0 0
#> 48.1 24.00 0 31 1 0
#> 200 24.00 0 64 0 0
#> 165.1 24.00 0 47 0 0
#> 12.3 24.00 0 63 0 0
#> 64.1 24.00 0 43 0 0
#> 121 24.00 0 57 1 0
#> 193 24.00 0 45 0 1
#> 161.1 24.00 0 45 0 0
#> 126.1 24.00 0 48 0 0
#> 87.1 24.00 0 27 0 0
#> 193.1 24.00 0 45 0 1
#> 191.1 24.00 0 60 0 1
#> 116 24.00 0 58 0 1
#> 161.2 24.00 0 45 0 0
#> 104 24.00 0 50 1 0
#> 9 24.00 0 31 1 0
#> 148 24.00 0 61 1 0
#> 53 24.00 0 32 0 1
#> 116.1 24.00 0 58 0 1
#> 74.2 24.00 0 43 0 1
#> 104.1 24.00 0 50 1 0
#> 1.2 24.00 0 23 1 0
#> 137 24.00 0 45 1 0
#> 141.2 24.00 0 44 1 0
#> 98 24.00 0 34 1 0
#> 147 24.00 0 76 1 0
#> 3 24.00 0 31 1 0
#> 152.2 24.00 0 36 0 1
#> 131 24.00 0 66 0 0
#> 163 24.00 0 66 0 0
#> 104.2 24.00 0 50 1 0
#> 2 24.00 0 9 0 0
#> 102.1 24.00 0 49 0 0
#> 12.4 24.00 0 63 0 0
#> 173.1 24.00 0 19 0 1
#> 186 24.00 0 45 1 0
#> 132.1 24.00 0 55 0 0
#> 121.1 24.00 0 57 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.547 NA NA NA
#> 2 age, Cure model 0.00914 NA NA NA
#> 3 grade_ii, Cure model 0.469 NA NA NA
#> 4 grade_iii, Cure model 0.667 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00912 NA NA NA
#> 2 grade_ii, Survival model 0.305 NA NA NA
#> 3 grade_iii, Survival model 0.611 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.546962 0.009141 0.469421 0.667345
#>
#> Degrees of Freedom: 193 Total (i.e. Null); 190 Residual
#> Null Deviance: 266.9
#> Residual Deviance: 262.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.546962394 0.009141198 0.469421496 0.667344960
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.009115672 0.305002683 0.610553684
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.1594952 0.1864463 0.7931911 0.8214706 0.8326357 0.2826976 0.9733738
#> [8] 0.9064202 0.5431294 0.4684355 0.9823393 0.8045887 0.9823393 0.9214457
#> [15] 0.8962265 0.8649482 0.9595757 0.7515652 0.4293369 0.2277068 0.8102571
#> [22] 0.8649482 0.6860289 0.5248311 0.5693982 0.8434524 0.6931208 0.2826976
#> [29] 0.7265213 0.5431294 0.7638133 0.5064044 0.7758381 0.0736517 0.6931208
#> [36] 0.5064044 0.6569820 0.6788820 0.8962265 0.6645075 0.9164830 0.9114686
#> [43] 0.6417864 0.7817231 0.9312172 0.7198494 0.4876022 0.4293369 0.5431294
#> [50] 0.9360385 0.3954737 0.5943231 0.8102571 0.5860119 0.8434524 0.7515652
#> [57] 0.9687793 0.2652590 0.6264405 0.3954737 0.9823393 0.9263567 0.7931911
#> [64] 0.4684355 0.6417864 0.5693982 0.6931208 0.9548954 0.8807172 0.3830024
#> [71] 0.7698680 0.3561059 0.8595880 0.8326357 0.3270872 0.3699314 0.4293369
#> [78] 0.8807172 0.4182696 0.9956030 0.4876022 0.8542189 0.6264405 0.1249163
#> [85] 0.7265213 0.8754635 0.7453345 0.6931208 0.9455147 0.6108069 0.6108069
#> [92] 0.6025951 0.5340373 0.2826976 0.9455147 0.7817231 0.6645075 0.9360385
#> [99] 0.8270812 0.2277068 0.9733738 0.8910723 0.3270872 0.1864463 0.4293369
#> [106] 0.7265213 0.9595757 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [183] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [190] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#>
#> $Time
#> 69 63 6 180 57 66 77 43 58 190 25 167 25.1
#> 23.23 22.77 15.64 14.82 14.46 22.13 7.27 12.10 19.34 20.81 6.32 15.55 6.32
#> 52 56 140 183 192 32 15 157 140.1 23 166 76 81
#> 10.42 12.21 12.68 9.24 16.44 20.90 22.68 15.10 12.68 16.92 19.98 19.22 14.06
#> 106 66.1 130 58.1 5 150 26 168 106.1 150.1 117 30 56.1
#> 16.67 22.13 16.47 19.34 16.43 20.33 15.77 23.72 16.67 20.33 17.46 17.43 12.21
#> 111 159 107 184 125 61 171 68 32.1 58.2 145 153 8
#> 17.45 10.55 11.18 17.77 15.65 10.12 16.57 20.62 20.90 19.34 10.07 21.33 18.43
#> 157.1 179 81.1 192.1 149 194 40 153.1 25.2 93 6.1 190.1 184.1
#> 15.10 18.63 14.06 16.44 8.37 22.40 18.00 21.33 6.32 10.33 15.64 20.81 17.77
#> 76.1 106.2 187 177 139 188 136 155 57.1 175 197 32.2 177.1
#> 19.22 16.67 9.92 12.53 21.49 16.16 21.83 13.08 14.46 21.91 21.60 20.90 12.53
#> 99 127 68.1 60 40.1 129 130.1 154 181 106.3 101 108 108.1
#> 21.19 3.53 20.62 13.15 18.00 23.41 16.47 12.63 16.46 16.67 9.97 18.29 18.29
#> 88 105 66.2 101.1 125.1 111.1 145.1 96 15.1 77.1 37 175.1 63.1
#> 18.37 19.75 22.13 9.97 15.65 17.45 10.07 14.54 22.68 7.27 12.52 21.91 22.77
#> 32.3 130.2 183.1 11 126 80 12 75 185 44 74 118 46
#> 20.90 16.47 9.24 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34 173 71 146 161 141 132 47 152 64 135 83 142
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 83.1 102 94 80.1 33 12.1 87 162 142.1 118.1 1 165 48
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 141.1 21 94.1 109 1.1 138 191 122 152.1 74.1 12.2 75.1 122.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 48.1 200 165.1 12.3 64.1 121 193 161.1 126.1 87.1 193.1 191.1 116
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 161.2 104 9 148 53 116.1 74.2 104.1 1.2 137 141.2 98 147
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3 152.2 131 163 104.2 2 102.1 12.4 173.1 186 132.1 121.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[28]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.007110993 0.664474765 0.420204127
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.557904577 0.008644677 0.023382921
#> grade_iii, Cure model
#> 1.092983627
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 134 17.81 1 47 1 0
#> 101 9.97 1 10 0 1
#> 16 8.71 1 71 0 1
#> 129 23.41 1 53 1 0
#> 195 11.76 1 NA 1 0
#> 123 13.00 1 44 1 0
#> 110 17.56 1 65 0 1
#> 177 12.53 1 75 0 0
#> 70 7.38 1 30 1 0
#> 184 17.77 1 38 0 0
#> 6 15.64 1 39 0 0
#> 63 22.77 1 31 1 0
#> 113 22.86 1 34 0 0
#> 105 19.75 1 60 0 0
#> 18 15.21 1 49 1 0
#> 113.1 22.86 1 34 0 0
#> 6.1 15.64 1 39 0 0
#> 57 14.46 1 45 0 1
#> 130 16.47 1 53 0 1
#> 150 20.33 1 48 0 0
#> 16.1 8.71 1 71 0 1
#> 13 14.34 1 54 0 1
#> 123.1 13.00 1 44 1 0
#> 42 12.43 1 49 0 1
#> 96 14.54 1 33 0 1
#> 86 23.81 1 58 0 1
#> 86.1 23.81 1 58 0 1
#> 96.1 14.54 1 33 0 1
#> 90 20.94 1 50 0 1
#> 100 16.07 1 60 0 0
#> 101.1 9.97 1 10 0 1
#> 90.1 20.94 1 50 0 1
#> 164 23.60 1 76 0 1
#> 97 19.14 1 65 0 1
#> 96.2 14.54 1 33 0 1
#> 41 18.02 1 40 1 0
#> 111 17.45 1 47 0 1
#> 4 17.64 1 NA 0 1
#> 56 12.21 1 60 0 0
#> 130.1 16.47 1 53 0 1
#> 187 9.92 1 39 1 0
#> 187.1 9.92 1 39 1 0
#> 77 7.27 1 67 0 1
#> 197 21.60 1 69 1 0
#> 25 6.32 1 34 1 0
#> 140 12.68 1 59 1 0
#> 194 22.40 1 38 0 1
#> 187.2 9.92 1 39 1 0
#> 24 23.89 1 38 0 0
#> 184.1 17.77 1 38 0 0
#> 184.2 17.77 1 38 0 0
#> 15 22.68 1 48 0 0
#> 68 20.62 1 44 0 0
#> 51 18.23 1 83 0 1
#> 61 10.12 1 36 0 1
#> 56.1 12.21 1 60 0 0
#> 56.2 12.21 1 60 0 0
#> 167 15.55 1 56 1 0
#> 45 17.42 1 54 0 1
#> 91 5.33 1 61 0 1
#> 194.1 22.40 1 38 0 1
#> 77.1 7.27 1 67 0 1
#> 61.1 10.12 1 36 0 1
#> 157 15.10 1 47 0 0
#> 51.1 18.23 1 83 0 1
#> 76 19.22 1 54 0 1
#> 8 18.43 1 32 0 0
#> 155 13.08 1 26 0 0
#> 180 14.82 1 37 0 0
#> 154 12.63 1 20 1 0
#> 139 21.49 1 63 1 0
#> 41.1 18.02 1 40 1 0
#> 155.1 13.08 1 26 0 0
#> 183 9.24 1 67 1 0
#> 41.2 18.02 1 40 1 0
#> 188 16.16 1 46 0 1
#> 166 19.98 1 48 0 0
#> 183.1 9.24 1 67 1 0
#> 125 15.65 1 67 1 0
#> 96.3 14.54 1 33 0 1
#> 194.2 22.40 1 38 0 1
#> 124 9.73 1 NA 1 0
#> 78 23.88 1 43 0 0
#> 187.3 9.92 1 39 1 0
#> 145 10.07 1 65 1 0
#> 181 16.46 1 45 0 1
#> 90.2 20.94 1 50 0 1
#> 23 16.92 1 61 0 0
#> 42.1 12.43 1 49 0 1
#> 59 10.16 1 NA 1 0
#> 49 12.19 1 48 1 0
#> 133 14.65 1 57 0 0
#> 139.1 21.49 1 63 1 0
#> 91.1 5.33 1 61 0 1
#> 110.1 17.56 1 65 0 1
#> 85 16.44 1 36 0 0
#> 66 22.13 1 53 0 0
#> 60 13.15 1 38 1 0
#> 90.3 20.94 1 50 0 1
#> 130.2 16.47 1 53 0 1
#> 175 21.91 1 43 0 0
#> 89 11.44 1 NA 0 0
#> 108 18.29 1 39 0 1
#> 113.2 22.86 1 34 0 0
#> 139.2 21.49 1 63 1 0
#> 150.1 20.33 1 48 0 0
#> 59.1 10.16 1 NA 1 0
#> 195.1 11.76 1 NA 1 0
#> 199 19.81 1 NA 0 1
#> 26 15.77 1 49 0 1
#> 26.1 15.77 1 49 0 1
#> 123.2 13.00 1 44 1 0
#> 126 24.00 0 48 0 0
#> 71 24.00 0 51 0 0
#> 31 24.00 0 36 0 1
#> 44 24.00 0 56 0 0
#> 141 24.00 0 44 1 0
#> 122 24.00 0 66 0 0
#> 1 24.00 0 23 1 0
#> 44.1 24.00 0 56 0 0
#> 46 24.00 0 71 0 0
#> 121 24.00 0 57 1 0
#> 20 24.00 0 46 1 0
#> 28 24.00 0 67 1 0
#> 21 24.00 0 47 0 0
#> 143 24.00 0 51 0 0
#> 11 24.00 0 42 0 1
#> 174 24.00 0 49 1 0
#> 191 24.00 0 60 0 1
#> 12 24.00 0 63 0 0
#> 198 24.00 0 66 0 1
#> 178 24.00 0 52 1 0
#> 95 24.00 0 68 0 1
#> 144 24.00 0 28 0 1
#> 122.1 24.00 0 66 0 0
#> 104 24.00 0 50 1 0
#> 17 24.00 0 38 0 1
#> 115 24.00 0 NA 1 0
#> 64 24.00 0 43 0 0
#> 132 24.00 0 55 0 0
#> 112 24.00 0 61 0 0
#> 20.1 24.00 0 46 1 0
#> 27 24.00 0 63 1 0
#> 80 24.00 0 41 0 0
#> 94 24.00 0 51 0 1
#> 75 24.00 0 21 1 0
#> 9 24.00 0 31 1 0
#> 126.1 24.00 0 48 0 0
#> 151 24.00 0 42 0 0
#> 75.1 24.00 0 21 1 0
#> 196 24.00 0 19 0 0
#> 84 24.00 0 39 0 1
#> 138 24.00 0 44 1 0
#> 64.1 24.00 0 43 0 0
#> 11.1 24.00 0 42 0 1
#> 109 24.00 0 48 0 0
#> 98 24.00 0 34 1 0
#> 160 24.00 0 31 1 0
#> 72 24.00 0 40 0 1
#> 116 24.00 0 58 0 1
#> 2 24.00 0 9 0 0
#> 118 24.00 0 44 1 0
#> 141.1 24.00 0 44 1 0
#> 33 24.00 0 53 0 0
#> 53 24.00 0 32 0 1
#> 141.2 24.00 0 44 1 0
#> 27.1 24.00 0 63 1 0
#> 98.1 24.00 0 34 1 0
#> 82 24.00 0 34 0 0
#> 44.2 24.00 0 56 0 0
#> 165 24.00 0 47 0 0
#> 112.1 24.00 0 61 0 0
#> 102 24.00 0 49 0 0
#> 46.1 24.00 0 71 0 0
#> 152 24.00 0 36 0 1
#> 67 24.00 0 25 0 0
#> 28.1 24.00 0 67 1 0
#> 7 24.00 0 37 1 0
#> 173 24.00 0 19 0 1
#> 185 24.00 0 44 1 0
#> 152.1 24.00 0 36 0 1
#> 102.1 24.00 0 49 0 0
#> 73 24.00 0 NA 0 1
#> 74 24.00 0 43 0 1
#> 28.2 24.00 0 67 1 0
#> 156 24.00 0 50 1 0
#> 143.1 24.00 0 51 0 0
#> 119 24.00 0 17 0 0
#> 118.1 24.00 0 44 1 0
#> 104.1 24.00 0 50 1 0
#> 142 24.00 0 53 0 0
#> 65 24.00 0 57 1 0
#> 64.2 24.00 0 43 0 0
#> 165.1 24.00 0 47 0 0
#> 156.1 24.00 0 50 1 0
#> 35 24.00 0 51 0 0
#> 131 24.00 0 66 0 0
#> 38 24.00 0 31 1 0
#> 135 24.00 0 58 1 0
#> 185.1 24.00 0 44 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.558 NA NA NA
#> 2 age, Cure model 0.00864 NA NA NA
#> 3 grade_ii, Cure model 0.0234 NA NA NA
#> 4 grade_iii, Cure model 1.09 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00711 NA NA NA
#> 2 grade_ii, Survival model 0.664 NA NA NA
#> 3 grade_iii, Survival model 0.420 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.557905 0.008645 0.023383 1.092984
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 261.7
#> Residual Deviance: 249.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.557904577 0.008644677 0.023382921 1.092983627
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.007110993 0.664474765 0.420204127
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.373459422 0.854396790 0.927404001 0.054386677 0.712749666 0.411661137
#> [7] 0.759921633 0.945625721 0.383064619 0.557537643 0.093809026 0.064746414
#> [13] 0.275024487 0.586914560 0.064746414 0.557537643 0.664341038 0.460317063
#> [19] 0.245936379 0.927404001 0.674075682 0.712749666 0.769392078 0.626192380
#> [25] 0.024533071 0.024533071 0.626192380 0.200691571 0.518435659 0.854396790
#> [31] 0.200691571 0.043334699 0.295034918 0.626192380 0.345100637 0.430990734
#> [37] 0.788182214 0.460317063 0.873041780 0.873041780 0.954730645 0.162776234
#> [43] 0.972872503 0.740995993 0.114595202 0.873041780 0.003397372 0.383064619
#> [49] 0.383064619 0.104051742 0.236361488 0.325158642 0.826073734 0.788182214
#> [55] 0.788182214 0.577100156 0.440746539 0.981941427 0.114595202 0.954730645
#> [61] 0.826073734 0.596668347 0.325158642 0.285036159 0.305047668 0.693468168
#> [67] 0.606467647 0.750499725 0.172972878 0.345100637 0.693468168 0.909211314
#> [73] 0.345100637 0.508648771 0.265137840 0.909211314 0.547752973 0.626192380
#> [79] 0.114595202 0.012594396 0.873041780 0.844936153 0.489081534 0.200691571
#> [85] 0.450494397 0.769392078 0.816549037 0.616303716 0.172972878 0.981941427
#> [91] 0.411661137 0.498843482 0.142318998 0.683805146 0.200691571 0.460317063
#> [97] 0.152457132 0.315127779 0.064746414 0.172972878 0.245936379 0.528287142
#> [103] 0.528287142 0.712749666 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 134 101 16 129 123 110 177 70 184 6 63 113 105
#> 17.81 9.97 8.71 23.41 13.00 17.56 12.53 7.38 17.77 15.64 22.77 22.86 19.75
#> 18 113.1 6.1 57 130 150 16.1 13 123.1 42 96 86 86.1
#> 15.21 22.86 15.64 14.46 16.47 20.33 8.71 14.34 13.00 12.43 14.54 23.81 23.81
#> 96.1 90 100 101.1 90.1 164 97 96.2 41 111 56 130.1 187
#> 14.54 20.94 16.07 9.97 20.94 23.60 19.14 14.54 18.02 17.45 12.21 16.47 9.92
#> 187.1 77 197 25 140 194 187.2 24 184.1 184.2 15 68 51
#> 9.92 7.27 21.60 6.32 12.68 22.40 9.92 23.89 17.77 17.77 22.68 20.62 18.23
#> 61 56.1 56.2 167 45 91 194.1 77.1 61.1 157 51.1 76 8
#> 10.12 12.21 12.21 15.55 17.42 5.33 22.40 7.27 10.12 15.10 18.23 19.22 18.43
#> 155 180 154 139 41.1 155.1 183 41.2 188 166 183.1 125 96.3
#> 13.08 14.82 12.63 21.49 18.02 13.08 9.24 18.02 16.16 19.98 9.24 15.65 14.54
#> 194.2 78 187.3 145 181 90.2 23 42.1 49 133 139.1 91.1 110.1
#> 22.40 23.88 9.92 10.07 16.46 20.94 16.92 12.43 12.19 14.65 21.49 5.33 17.56
#> 85 66 60 90.3 130.2 175 108 113.2 139.2 150.1 26 26.1 123.2
#> 16.44 22.13 13.15 20.94 16.47 21.91 18.29 22.86 21.49 20.33 15.77 15.77 13.00
#> 126 71 31 44 141 122 1 44.1 46 121 20 28 21
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143 11 174 191 12 198 178 95 144 122.1 104 17 64
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 132 112 20.1 27 80 94 75 9 126.1 151 75.1 196 84
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 138 64.1 11.1 109 98 160 72 116 2 118 141.1 33 53
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 141.2 27.1 98.1 82 44.2 165 112.1 102 46.1 152 67 28.1 7
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 173 185 152.1 102.1 74 28.2 156 143.1 119 118.1 104.1 142 65
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64.2 165.1 156.1 35 131 38 135 185.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[29]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.005792526 0.817916977 0.528187692
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.5930496393 -0.0005972224 0.9893674668
#> grade_iii, Cure model
#> 1.5371338509
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 42 12.43 1 49 0 1
#> 32 20.90 1 37 1 0
#> 43 12.10 1 61 0 1
#> 24 23.89 1 38 0 0
#> 15 22.68 1 48 0 0
#> 108 18.29 1 39 0 1
#> 177 12.53 1 75 0 0
#> 52 10.42 1 52 0 1
#> 52.1 10.42 1 52 0 1
#> 43.1 12.10 1 61 0 1
#> 10 10.53 1 34 0 0
#> 158 20.14 1 74 1 0
#> 93 10.33 1 52 0 1
#> 60 13.15 1 38 1 0
#> 25 6.32 1 34 1 0
#> 40 18.00 1 28 1 0
#> 89 11.44 1 NA 0 0
#> 96 14.54 1 33 0 1
#> 70 7.38 1 30 1 0
#> 97 19.14 1 65 0 1
#> 43.2 12.10 1 61 0 1
#> 88 18.37 1 47 0 0
#> 106 16.67 1 49 1 0
#> 168 23.72 1 70 0 0
#> 107 11.18 1 54 1 0
#> 130 16.47 1 53 0 1
#> 45 17.42 1 54 0 1
#> 139 21.49 1 63 1 0
#> 125 15.65 1 67 1 0
#> 192 16.44 1 31 1 0
#> 197 21.60 1 69 1 0
#> 123 13.00 1 44 1 0
#> 61 10.12 1 36 0 1
#> 63 22.77 1 31 1 0
#> 76 19.22 1 54 0 1
#> 52.2 10.42 1 52 0 1
#> 101 9.97 1 10 0 1
#> 85 16.44 1 36 0 0
#> 179 18.63 1 42 0 0
#> 167 15.55 1 56 1 0
#> 69 23.23 1 25 0 1
#> 70.1 7.38 1 30 1 0
#> 124 9.73 1 NA 1 0
#> 78 23.88 1 43 0 0
#> 50 10.02 1 NA 1 0
#> 76.1 19.22 1 54 0 1
#> 52.3 10.42 1 52 0 1
#> 187 9.92 1 39 1 0
#> 154 12.63 1 20 1 0
#> 41 18.02 1 40 1 0
#> 25.1 6.32 1 34 1 0
#> 25.2 6.32 1 34 1 0
#> 127 3.53 1 62 0 1
#> 154.1 12.63 1 20 1 0
#> 69.1 23.23 1 25 0 1
#> 158.1 20.14 1 74 1 0
#> 130.1 16.47 1 53 0 1
#> 133 14.65 1 57 0 0
#> 158.2 20.14 1 74 1 0
#> 70.2 7.38 1 30 1 0
#> 6 15.64 1 39 0 0
#> 158.3 20.14 1 74 1 0
#> 183 9.24 1 67 1 0
#> 18 15.21 1 49 1 0
#> 68 20.62 1 44 0 0
#> 153 21.33 1 55 1 0
#> 32.1 20.90 1 37 1 0
#> 168.1 23.72 1 70 0 0
#> 153.1 21.33 1 55 1 0
#> 4 17.64 1 NA 0 1
#> 66 22.13 1 53 0 0
#> 164 23.60 1 76 0 1
#> 101.1 9.97 1 10 0 1
#> 55 19.34 1 69 0 1
#> 177.1 12.53 1 75 0 0
#> 171 16.57 1 41 0 1
#> 117 17.46 1 26 0 1
#> 171.1 16.57 1 41 0 1
#> 128 20.35 1 35 0 1
#> 123.1 13.00 1 44 1 0
#> 6.1 15.64 1 39 0 0
#> 52.4 10.42 1 52 0 1
#> 26 15.77 1 49 0 1
#> 15.1 22.68 1 48 0 0
#> 69.2 23.23 1 25 0 1
#> 136 21.83 1 43 0 1
#> 145 10.07 1 65 1 0
#> 180 14.82 1 37 0 0
#> 181 16.46 1 45 0 1
#> 145.1 10.07 1 65 1 0
#> 93.1 10.33 1 52 0 1
#> 70.3 7.38 1 30 1 0
#> 79 16.23 1 54 1 0
#> 157 15.10 1 47 0 0
#> 45.1 17.42 1 54 0 1
#> 55.1 19.34 1 69 0 1
#> 101.2 9.97 1 10 0 1
#> 55.2 19.34 1 69 0 1
#> 194 22.40 1 38 0 1
#> 179.1 18.63 1 42 0 0
#> 149 8.37 1 33 1 0
#> 190 20.81 1 42 1 0
#> 16 8.71 1 71 0 1
#> 57 14.46 1 45 0 1
#> 106.1 16.67 1 49 1 0
#> 90 20.94 1 50 0 1
#> 23 16.92 1 61 0 0
#> 195 11.76 1 NA 1 0
#> 92 22.92 1 47 0 1
#> 23.1 16.92 1 61 0 0
#> 136.1 21.83 1 43 0 1
#> 114 13.68 1 NA 0 0
#> 28 24.00 0 67 1 0
#> 20 24.00 0 46 1 0
#> 161 24.00 0 45 0 0
#> 98 24.00 0 34 1 0
#> 185 24.00 0 44 1 0
#> 193 24.00 0 45 0 1
#> 165 24.00 0 47 0 0
#> 31 24.00 0 36 0 1
#> 94 24.00 0 51 0 1
#> 185.1 24.00 0 44 1 0
#> 161.1 24.00 0 45 0 0
#> 200 24.00 0 64 0 0
#> 191 24.00 0 60 0 1
#> 143 24.00 0 51 0 0
#> 3 24.00 0 31 1 0
#> 142 24.00 0 53 0 0
#> 147 24.00 0 76 1 0
#> 160 24.00 0 31 1 0
#> 151 24.00 0 42 0 0
#> 156 24.00 0 50 1 0
#> 163 24.00 0 66 0 0
#> 83 24.00 0 6 0 0
#> 143.1 24.00 0 51 0 0
#> 44 24.00 0 56 0 0
#> 144 24.00 0 28 0 1
#> 95 24.00 0 68 0 1
#> 21 24.00 0 47 0 0
#> 53 24.00 0 32 0 1
#> 185.2 24.00 0 44 1 0
#> 198 24.00 0 66 0 1
#> 126 24.00 0 48 0 0
#> 82 24.00 0 34 0 0
#> 84 24.00 0 39 0 1
#> 27 24.00 0 63 1 0
#> 200.1 24.00 0 64 0 0
#> 33 24.00 0 53 0 0
#> 163.1 24.00 0 66 0 0
#> 34 24.00 0 36 0 0
#> 84.1 24.00 0 39 0 1
#> 73 24.00 0 NA 0 1
#> 132 24.00 0 55 0 0
#> 141 24.00 0 44 1 0
#> 20.1 24.00 0 46 1 0
#> 103 24.00 0 56 1 0
#> 196 24.00 0 19 0 0
#> 200.2 24.00 0 64 0 0
#> 33.1 24.00 0 53 0 0
#> 152 24.00 0 36 0 1
#> 141.1 24.00 0 44 1 0
#> 147.1 24.00 0 76 1 0
#> 102 24.00 0 49 0 0
#> 54 24.00 0 53 1 0
#> 3.1 24.00 0 31 1 0
#> 191.1 24.00 0 60 0 1
#> 9 24.00 0 31 1 0
#> 178 24.00 0 52 1 0
#> 27.1 24.00 0 63 1 0
#> 126.1 24.00 0 48 0 0
#> 46 24.00 0 71 0 0
#> 94.1 24.00 0 51 0 1
#> 44.1 24.00 0 56 0 0
#> 120 24.00 0 68 0 1
#> 74 24.00 0 43 0 1
#> 143.2 24.00 0 51 0 0
#> 34.1 24.00 0 36 0 0
#> 83.1 24.00 0 6 0 0
#> 156.1 24.00 0 50 1 0
#> 80 24.00 0 41 0 0
#> 196.1 24.00 0 19 0 0
#> 104 24.00 0 50 1 0
#> 71 24.00 0 51 0 0
#> 132.1 24.00 0 55 0 0
#> 34.2 24.00 0 36 0 0
#> 75 24.00 0 21 1 0
#> 62 24.00 0 71 0 0
#> 147.2 24.00 0 76 1 0
#> 44.2 24.00 0 56 0 0
#> 33.2 24.00 0 53 0 0
#> 47 24.00 0 38 0 1
#> 173 24.00 0 19 0 1
#> 163.2 24.00 0 66 0 0
#> 122 24.00 0 66 0 0
#> 73.1 24.00 0 NA 0 1
#> 64 24.00 0 43 0 0
#> 28.1 24.00 0 67 1 0
#> 104.1 24.00 0 50 1 0
#> 152.1 24.00 0 36 0 1
#> 163.3 24.00 0 66 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.593 NA NA NA
#> 2 age, Cure model -0.000597 NA NA NA
#> 3 grade_ii, Cure model 0.989 NA NA NA
#> 4 grade_iii, Cure model 1.54 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00579 NA NA NA
#> 2 grade_ii, Survival model 0.818 NA NA NA
#> 3 grade_iii, Survival model 0.528 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.5930496 -0.0005972 0.9893675 1.5371339
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.1
#> Residual Deviance: 246.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.5930496393 -0.0005972224 0.9893674668 1.5371338509
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.005792526 0.817916977 0.528187692
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.769268788 0.291180385 0.777179241 0.005437231 0.156542018 0.463494364
#> [7] 0.753484532 0.816172213 0.816172213 0.777179241 0.808346876 0.342608145
#> [13] 0.854101676 0.713610754 0.972166655 0.482172128 0.697044776 0.943954491
#> [19] 0.425993257 0.777179241 0.454014045 0.535960628 0.035574340 0.800535059
#> [25] 0.570790868 0.500302032 0.245786225 0.630433064 0.596606098 0.233417984
#> [31] 0.721801191 0.869410293 0.143605834 0.407432400 0.816172213 0.892185807
#> [37] 0.596606098 0.435343315 0.655503415 0.090669399 0.943954491 0.018906223
#> [43] 0.407432400 0.816172213 0.914420913 0.737815944 0.472906745 0.972166655
#> [49] 0.972166655 0.993011571 0.737815944 0.090669399 0.342608145 0.570790868
#> [55] 0.688707092 0.342608145 0.943954491 0.638797051 0.342608145 0.921844520
#> [61] 0.663842268 0.322094157 0.257808021 0.291180385 0.035574340 0.257808021
#> [67] 0.195392437 0.070645134 0.892185807 0.379609850 0.753484532 0.553468146
#> [73] 0.491275442 0.553468146 0.332412001 0.721801191 0.638797051 0.816172213
#> [79] 0.622009066 0.156542018 0.090669399 0.208675071 0.877073074 0.680397697
#> [85] 0.587984465 0.877073074 0.854101676 0.943954491 0.613553373 0.672107833
#> [91] 0.500302032 0.379609850 0.892185807 0.379609850 0.182344527 0.435343315
#> [97] 0.936620525 0.311850163 0.929236165 0.705342682 0.535960628 0.279985008
#> [103] 0.518039983 0.129539445 0.518039983 0.208675071 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 42 32 43 24 15 108 177 52 52.1 43.1 10 158 93
#> 12.43 20.90 12.10 23.89 22.68 18.29 12.53 10.42 10.42 12.10 10.53 20.14 10.33
#> 60 25 40 96 70 97 43.2 88 106 168 107 130 45
#> 13.15 6.32 18.00 14.54 7.38 19.14 12.10 18.37 16.67 23.72 11.18 16.47 17.42
#> 139 125 192 197 123 61 63 76 52.2 101 85 179 167
#> 21.49 15.65 16.44 21.60 13.00 10.12 22.77 19.22 10.42 9.97 16.44 18.63 15.55
#> 69 70.1 78 76.1 52.3 187 154 41 25.1 25.2 127 154.1 69.1
#> 23.23 7.38 23.88 19.22 10.42 9.92 12.63 18.02 6.32 6.32 3.53 12.63 23.23
#> 158.1 130.1 133 158.2 70.2 6 158.3 183 18 68 153 32.1 168.1
#> 20.14 16.47 14.65 20.14 7.38 15.64 20.14 9.24 15.21 20.62 21.33 20.90 23.72
#> 153.1 66 164 101.1 55 177.1 171 117 171.1 128 123.1 6.1 52.4
#> 21.33 22.13 23.60 9.97 19.34 12.53 16.57 17.46 16.57 20.35 13.00 15.64 10.42
#> 26 15.1 69.2 136 145 180 181 145.1 93.1 70.3 79 157 45.1
#> 15.77 22.68 23.23 21.83 10.07 14.82 16.46 10.07 10.33 7.38 16.23 15.10 17.42
#> 55.1 101.2 55.2 194 179.1 149 190 16 57 106.1 90 23 92
#> 19.34 9.97 19.34 22.40 18.63 8.37 20.81 8.71 14.46 16.67 20.94 16.92 22.92
#> 23.1 136.1 28 20 161 98 185 193 165 31 94 185.1 161.1
#> 16.92 21.83 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 200 191 143 3 142 147 160 151 156 163 83 143.1 44
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 144 95 21 53 185.2 198 126 82 84 27 200.1 33 163.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34 84.1 132 141 20.1 103 196 200.2 33.1 152 141.1 147.1 102
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 54 3.1 191.1 9 178 27.1 126.1 46 94.1 44.1 120 74 143.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34.1 83.1 156.1 80 196.1 104 71 132.1 34.2 75 62 147.2 44.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33.2 47 173 163.2 122 64 28.1 104.1 152.1 163.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[30]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.001642449 0.858633056 0.529602171
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.87592151 0.01233655 0.26890717
#> grade_iii, Cure model
#> 1.20277635
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 168 23.72 1 70 0 0
#> 183 9.24 1 67 1 0
#> 68 20.62 1 44 0 0
#> 39 15.59 1 37 0 1
#> 93 10.33 1 52 0 1
#> 91 5.33 1 61 0 1
#> 68.1 20.62 1 44 0 0
#> 86 23.81 1 58 0 1
#> 170 19.54 1 43 0 1
#> 113 22.86 1 34 0 0
#> 25 6.32 1 34 1 0
#> 18 15.21 1 49 1 0
#> 50 10.02 1 NA 1 0
#> 52 10.42 1 52 0 1
#> 56 12.21 1 60 0 0
#> 111 17.45 1 47 0 1
#> 154 12.63 1 20 1 0
#> 188 16.16 1 46 0 1
#> 4 17.64 1 NA 0 1
#> 123 13.00 1 44 1 0
#> 159 10.55 1 50 0 1
#> 26 15.77 1 49 0 1
#> 125 15.65 1 67 1 0
#> 101 9.97 1 10 0 1
#> 14 12.89 1 21 0 0
#> 96 14.54 1 33 0 1
#> 4.1 17.64 1 NA 0 1
#> 184 17.77 1 38 0 0
#> 86.1 23.81 1 58 0 1
#> 168.1 23.72 1 70 0 0
#> 140 12.68 1 59 1 0
#> 155 13.08 1 26 0 0
#> 96.1 14.54 1 33 0 1
#> 63 22.77 1 31 1 0
#> 58 19.34 1 39 0 0
#> 59 10.16 1 NA 1 0
#> 63.1 22.77 1 31 1 0
#> 128 20.35 1 35 0 1
#> 63.2 22.77 1 31 1 0
#> 194 22.40 1 38 0 1
#> 5 16.43 1 51 0 1
#> 25.1 6.32 1 34 1 0
#> 158 20.14 1 74 1 0
#> 92 22.92 1 47 0 1
#> 195 11.76 1 NA 1 0
#> 194.1 22.40 1 38 0 1
#> 45 17.42 1 54 0 1
#> 108 18.29 1 39 0 1
#> 43 12.10 1 61 0 1
#> 93.1 10.33 1 52 0 1
#> 164 23.60 1 76 0 1
#> 89 11.44 1 NA 0 0
#> 78 23.88 1 43 0 0
#> 110 17.56 1 65 0 1
#> 81 14.06 1 34 0 0
#> 149 8.37 1 33 1 0
#> 57 14.46 1 45 0 1
#> 18.1 15.21 1 49 1 0
#> 13 14.34 1 54 0 1
#> 97 19.14 1 65 0 1
#> 184.1 17.77 1 38 0 0
#> 179 18.63 1 42 0 0
#> 24 23.89 1 38 0 0
#> 39.1 15.59 1 37 0 1
#> 36 21.19 1 48 0 1
#> 23 16.92 1 61 0 0
#> 106 16.67 1 49 1 0
#> 15 22.68 1 48 0 0
#> 90 20.94 1 50 0 1
#> 150 20.33 1 48 0 0
#> 10 10.53 1 34 0 0
#> 32 20.90 1 37 1 0
#> 58.1 19.34 1 39 0 0
#> 125.1 15.65 1 67 1 0
#> 77 7.27 1 67 0 1
#> 32.1 20.90 1 37 1 0
#> 90.1 20.94 1 50 0 1
#> 56.1 12.21 1 60 0 0
#> 77.1 7.27 1 67 0 1
#> 167 15.55 1 56 1 0
#> 68.2 20.62 1 44 0 0
#> 43.1 12.10 1 61 0 1
#> 68.3 20.62 1 44 0 0
#> 183.1 9.24 1 67 1 0
#> 92.1 22.92 1 47 0 1
#> 4.2 17.64 1 NA 0 1
#> 16 8.71 1 71 0 1
#> 154.1 12.63 1 20 1 0
#> 166 19.98 1 48 0 0
#> 66 22.13 1 53 0 0
#> 40 18.00 1 28 1 0
#> 76 19.22 1 54 0 1
#> 61 10.12 1 36 0 1
#> 90.2 20.94 1 50 0 1
#> 99 21.19 1 38 0 1
#> 24.1 23.89 1 38 0 0
#> 50.1 10.02 1 NA 1 0
#> 123.1 13.00 1 44 1 0
#> 26.1 15.77 1 49 0 1
#> 55 19.34 1 69 0 1
#> 25.2 6.32 1 34 1 0
#> 5.1 16.43 1 51 0 1
#> 150.1 20.33 1 48 0 0
#> 61.1 10.12 1 36 0 1
#> 92.2 22.92 1 47 0 1
#> 159.1 10.55 1 50 0 1
#> 140.1 12.68 1 59 1 0
#> 130 16.47 1 53 0 1
#> 101.1 9.97 1 10 0 1
#> 199 19.81 1 NA 0 1
#> 88 18.37 1 47 0 0
#> 114 13.68 1 NA 0 0
#> 116 24.00 0 58 0 1
#> 193 24.00 0 45 0 1
#> 186 24.00 0 45 1 0
#> 178 24.00 0 52 1 0
#> 20 24.00 0 46 1 0
#> 33 24.00 0 53 0 0
#> 151 24.00 0 42 0 0
#> 162 24.00 0 51 0 0
#> 1 24.00 0 23 1 0
#> 27 24.00 0 63 1 0
#> 7 24.00 0 37 1 0
#> 115 24.00 0 NA 1 0
#> 115.1 24.00 0 NA 1 0
#> 161 24.00 0 45 0 0
#> 162.1 24.00 0 51 0 0
#> 28 24.00 0 67 1 0
#> 144 24.00 0 28 0 1
#> 53 24.00 0 32 0 1
#> 54 24.00 0 53 1 0
#> 119 24.00 0 17 0 0
#> 131 24.00 0 66 0 0
#> 80 24.00 0 41 0 0
#> 191 24.00 0 60 0 1
#> 83 24.00 0 6 0 0
#> 152 24.00 0 36 0 1
#> 173 24.00 0 19 0 1
#> 7.1 24.00 0 37 1 0
#> 132 24.00 0 55 0 0
#> 156 24.00 0 50 1 0
#> 73 24.00 0 NA 0 1
#> 163 24.00 0 66 0 0
#> 176 24.00 0 43 0 1
#> 200 24.00 0 64 0 0
#> 84 24.00 0 39 0 1
#> 141 24.00 0 44 1 0
#> 31 24.00 0 36 0 1
#> 152.1 24.00 0 36 0 1
#> 174 24.00 0 49 1 0
#> 137 24.00 0 45 1 0
#> 163.1 24.00 0 66 0 0
#> 186.1 24.00 0 45 1 0
#> 71 24.00 0 51 0 0
#> 34 24.00 0 36 0 0
#> 65 24.00 0 57 1 0
#> 34.1 24.00 0 36 0 0
#> 122 24.00 0 66 0 0
#> 21 24.00 0 47 0 0
#> 84.1 24.00 0 39 0 1
#> 31.1 24.00 0 36 0 1
#> 162.2 24.00 0 51 0 0
#> 132.1 24.00 0 55 0 0
#> 80.1 24.00 0 41 0 0
#> 182 24.00 0 35 0 0
#> 126 24.00 0 48 0 0
#> 135 24.00 0 58 1 0
#> 116.1 24.00 0 58 0 1
#> 196 24.00 0 19 0 0
#> 2 24.00 0 9 0 0
#> 87 24.00 0 27 0 0
#> 1.1 24.00 0 23 1 0
#> 102 24.00 0 49 0 0
#> 22 24.00 0 52 1 0
#> 132.2 24.00 0 55 0 0
#> 12 24.00 0 63 0 0
#> 103 24.00 0 56 1 0
#> 33.1 24.00 0 53 0 0
#> 95 24.00 0 68 0 1
#> 121 24.00 0 57 1 0
#> 119.1 24.00 0 17 0 0
#> 7.2 24.00 0 37 1 0
#> 34.2 24.00 0 36 0 0
#> 28.1 24.00 0 67 1 0
#> 75 24.00 0 21 1 0
#> 156.1 24.00 0 50 1 0
#> 64 24.00 0 43 0 0
#> 31.2 24.00 0 36 0 1
#> 20.1 24.00 0 46 1 0
#> 83.1 24.00 0 6 0 0
#> 84.2 24.00 0 39 0 1
#> 80.2 24.00 0 41 0 0
#> 71.1 24.00 0 51 0 0
#> 64.1 24.00 0 43 0 0
#> 152.2 24.00 0 36 0 1
#> 182.1 24.00 0 35 0 0
#> 142 24.00 0 53 0 0
#> 17 24.00 0 38 0 1
#> 186.2 24.00 0 45 1 0
#> 11 24.00 0 42 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.876 NA NA NA
#> 2 age, Cure model 0.0123 NA NA NA
#> 3 grade_ii, Cure model 0.269 NA NA NA
#> 4 grade_iii, Cure model 1.20 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00164 NA NA NA
#> 2 grade_ii, Survival model 0.859 NA NA NA
#> 3 grade_iii, Survival model 0.530 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.87592 0.01234 0.26891 1.20278
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 257.7
#> Residual Deviance: 243.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.87592151 0.01233655 0.26890717 1.20277635
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.001642449 0.858633056 0.529602171
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.12374563 0.93545115 0.39363121 0.70392883 0.89480870 0.99367786
#> [7] 0.39363121 0.08816143 0.48126150 0.22216059 0.97476775 0.72779318
#> [13] 0.88788638 0.83902478 0.60165625 0.82495282 0.66268882 0.78851057
#> [19] 0.86708927 0.67116097 0.68776224 0.92203267 0.80319000 0.74314946
#> [25] 0.57461205 0.08816143 0.12374563 0.81056586 0.78096773 0.74314946
#> [31] 0.23764430 0.49085349 0.23764430 0.43236047 0.23764430 0.28551847
#> [37] 0.64572903 0.97476775 0.46186736 0.17902440 0.28551847 0.61059235
#> [43] 0.55628544 0.85311892 0.89480870 0.16054830 0.06176884 0.59264356
#> [49] 0.77342794 0.95526187 0.75831501 0.72779318 0.76589213 0.52827418
#> [55] 0.57461205 0.53760012 0.02130618 0.70392883 0.32046103 0.61945658
#> [61] 0.62833292 0.27310389 0.34273167 0.44224782 0.88093375 0.37390568
#> [67] 0.49085349 0.68776224 0.96180924 0.37390568 0.34273167 0.83902478
#> [73] 0.96180924 0.71987638 0.39363121 0.85311892 0.39363121 0.93545115
#> [79] 0.17902440 0.94865859 0.82495282 0.47155687 0.30863839 0.56554181
#> [85] 0.51886080 0.90848194 0.34273167 0.32046103 0.02130618 0.78851057
#> [91] 0.67116097 0.49085349 0.97476775 0.64572903 0.44224782 0.90848194
#> [97] 0.17902440 0.86708927 0.81056586 0.63706403 0.92203267 0.54693685
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000
#>
#> $Time
#> 168 183 68 39 93 91 68.1 86 170 113 25 18 52
#> 23.72 9.24 20.62 15.59 10.33 5.33 20.62 23.81 19.54 22.86 6.32 15.21 10.42
#> 56 111 154 188 123 159 26 125 101 14 96 184 86.1
#> 12.21 17.45 12.63 16.16 13.00 10.55 15.77 15.65 9.97 12.89 14.54 17.77 23.81
#> 168.1 140 155 96.1 63 58 63.1 128 63.2 194 5 25.1 158
#> 23.72 12.68 13.08 14.54 22.77 19.34 22.77 20.35 22.77 22.40 16.43 6.32 20.14
#> 92 194.1 45 108 43 93.1 164 78 110 81 149 57 18.1
#> 22.92 22.40 17.42 18.29 12.10 10.33 23.60 23.88 17.56 14.06 8.37 14.46 15.21
#> 13 97 184.1 179 24 39.1 36 23 106 15 90 150 10
#> 14.34 19.14 17.77 18.63 23.89 15.59 21.19 16.92 16.67 22.68 20.94 20.33 10.53
#> 32 58.1 125.1 77 32.1 90.1 56.1 77.1 167 68.2 43.1 68.3 183.1
#> 20.90 19.34 15.65 7.27 20.90 20.94 12.21 7.27 15.55 20.62 12.10 20.62 9.24
#> 92.1 16 154.1 166 66 40 76 61 90.2 99 24.1 123.1 26.1
#> 22.92 8.71 12.63 19.98 22.13 18.00 19.22 10.12 20.94 21.19 23.89 13.00 15.77
#> 55 25.2 5.1 150.1 61.1 92.2 159.1 140.1 130 101.1 88 116 193
#> 19.34 6.32 16.43 20.33 10.12 22.92 10.55 12.68 16.47 9.97 18.37 24.00 24.00
#> 186 178 20 33 151 162 1 27 7 161 162.1 28 144
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53 54 119 131 80 191 83 152 173 7.1 132 156 163
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176 200 84 141 31 152.1 174 137 163.1 186.1 71 34 65
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34.1 122 21 84.1 31.1 162.2 132.1 80.1 182 126 135 116.1 196
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 2 87 1.1 102 22 132.2 12 103 33.1 95 121 119.1 7.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34.2 28.1 75 156.1 64 31.2 20.1 83.1 84.2 80.2 71.1 64.1 152.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 182.1 142 17 186.2 11
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[31]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.006601053 0.571517716 0.212276511
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.28143339 0.02404753 0.18374711
#> grade_iii, Cure model
#> 0.90373168
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 69 23.23 1 25 0 1
#> 60 13.15 1 38 1 0
#> 127 3.53 1 62 0 1
#> 101 9.97 1 10 0 1
#> 187 9.92 1 39 1 0
#> 164 23.60 1 76 0 1
#> 175 21.91 1 43 0 0
#> 93 10.33 1 52 0 1
#> 96 14.54 1 33 0 1
#> 41 18.02 1 40 1 0
#> 189 10.51 1 NA 1 0
#> 50 10.02 1 NA 1 0
#> 39 15.59 1 37 0 1
#> 155 13.08 1 26 0 0
#> 134 17.81 1 47 1 0
#> 23 16.92 1 61 0 0
#> 60.1 13.15 1 38 1 0
#> 57 14.46 1 45 0 1
#> 99 21.19 1 38 0 1
#> 89 11.44 1 NA 0 0
#> 78 23.88 1 43 0 0
#> 106 16.67 1 49 1 0
#> 130 16.47 1 53 0 1
#> 43 12.10 1 61 0 1
#> 40 18.00 1 28 1 0
#> 155.1 13.08 1 26 0 0
#> 57.1 14.46 1 45 0 1
#> 184 17.77 1 38 0 0
#> 85 16.44 1 36 0 0
#> 197 21.60 1 69 1 0
#> 6 15.64 1 39 0 0
#> 18 15.21 1 49 1 0
#> 139 21.49 1 63 1 0
#> 68 20.62 1 44 0 0
#> 50.1 10.02 1 NA 1 0
#> 199 19.81 1 NA 0 1
#> 68.1 20.62 1 44 0 0
#> 181 16.46 1 45 0 1
#> 129 23.41 1 53 1 0
#> 159 10.55 1 50 0 1
#> 195 11.76 1 NA 1 0
#> 180 14.82 1 37 0 0
#> 166 19.98 1 48 0 0
#> 32 20.90 1 37 1 0
#> 49 12.19 1 48 1 0
#> 36 21.19 1 48 0 1
#> 166.1 19.98 1 48 0 0
#> 26 15.77 1 49 0 1
#> 16 8.71 1 71 0 1
#> 177 12.53 1 75 0 0
#> 86 23.81 1 58 0 1
#> 25 6.32 1 34 1 0
#> 123 13.00 1 44 1 0
#> 58 19.34 1 39 0 0
#> 130.1 16.47 1 53 0 1
#> 183 9.24 1 67 1 0
#> 197.1 21.60 1 69 1 0
#> 51 18.23 1 83 0 1
#> 55 19.34 1 69 0 1
#> 123.1 13.00 1 44 1 0
#> 124 9.73 1 NA 1 0
#> 177.1 12.53 1 75 0 0
#> 129.1 23.41 1 53 1 0
#> 32.1 20.90 1 37 1 0
#> 199.1 19.81 1 NA 0 1
#> 181.1 16.46 1 45 0 1
#> 37 12.52 1 57 1 0
#> 153 21.33 1 55 1 0
#> 169 22.41 1 46 0 0
#> 125 15.65 1 67 1 0
#> 101.1 9.97 1 10 0 1
#> 49.1 12.19 1 48 1 0
#> 36.1 21.19 1 48 0 1
#> 86.1 23.81 1 58 0 1
#> 86.2 23.81 1 58 0 1
#> 145 10.07 1 65 1 0
#> 99.1 21.19 1 38 0 1
#> 149 8.37 1 33 1 0
#> 167 15.55 1 56 1 0
#> 26.1 15.77 1 49 0 1
#> 58.1 19.34 1 39 0 0
#> 41.1 18.02 1 40 1 0
#> 78.1 23.88 1 43 0 0
#> 61 10.12 1 36 0 1
#> 169.1 22.41 1 46 0 0
#> 92 22.92 1 47 0 1
#> 29 15.45 1 68 1 0
#> 89.1 11.44 1 NA 0 0
#> 125.1 15.65 1 67 1 0
#> 66 22.13 1 53 0 0
#> 170 19.54 1 43 0 1
#> 16.1 8.71 1 71 0 1
#> 50.2 10.02 1 NA 1 0
#> 183.1 9.24 1 67 1 0
#> 40.1 18.00 1 28 1 0
#> 8 18.43 1 32 0 0
#> 136 21.83 1 43 0 1
#> 183.2 9.24 1 67 1 0
#> 150 20.33 1 48 0 0
#> 63 22.77 1 31 1 0
#> 56 12.21 1 60 0 0
#> 86.3 23.81 1 58 0 1
#> 70 7.38 1 30 1 0
#> 42 12.43 1 49 0 1
#> 61.1 10.12 1 36 0 1
#> 55.1 19.34 1 69 0 1
#> 37.1 12.52 1 57 1 0
#> 167.1 15.55 1 56 1 0
#> 36.2 21.19 1 48 0 1
#> 159.1 10.55 1 50 0 1
#> 76 19.22 1 54 0 1
#> 30 17.43 1 78 0 0
#> 22 24.00 0 52 1 0
#> 1 24.00 0 23 1 0
#> 144 24.00 0 28 0 1
#> 200 24.00 0 64 0 0
#> 87 24.00 0 27 0 0
#> 173 24.00 0 19 0 1
#> 182 24.00 0 35 0 0
#> 186 24.00 0 45 1 0
#> 27 24.00 0 63 1 0
#> 75 24.00 0 21 1 0
#> 196 24.00 0 19 0 0
#> 186.1 24.00 0 45 1 0
#> 94 24.00 0 51 0 1
#> 12 24.00 0 63 0 0
#> 193 24.00 0 45 0 1
#> 146 24.00 0 63 1 0
#> 98 24.00 0 34 1 0
#> 73 24.00 0 NA 0 1
#> 11 24.00 0 42 0 1
#> 74 24.00 0 43 0 1
#> 178 24.00 0 52 1 0
#> 95 24.00 0 68 0 1
#> 64 24.00 0 43 0 0
#> 118 24.00 0 44 1 0
#> 185 24.00 0 44 1 0
#> 141 24.00 0 44 1 0
#> 118.1 24.00 0 44 1 0
#> 200.1 24.00 0 64 0 0
#> 3 24.00 0 31 1 0
#> 121 24.00 0 57 1 0
#> 35 24.00 0 51 0 0
#> 82 24.00 0 34 0 0
#> 48 24.00 0 31 1 0
#> 12.1 24.00 0 63 0 0
#> 144.1 24.00 0 28 0 1
#> 174 24.00 0 49 1 0
#> 80 24.00 0 41 0 0
#> 35.1 24.00 0 51 0 0
#> 47 24.00 0 38 0 1
#> 7 24.00 0 37 1 0
#> 27.1 24.00 0 63 1 0
#> 71 24.00 0 51 0 0
#> 198 24.00 0 66 0 1
#> 82.1 24.00 0 34 0 0
#> 20 24.00 0 46 1 0
#> 186.2 24.00 0 45 1 0
#> 109 24.00 0 48 0 0
#> 12.2 24.00 0 63 0 0
#> 35.2 24.00 0 51 0 0
#> 3.1 24.00 0 31 1 0
#> 64.1 24.00 0 43 0 0
#> 19 24.00 0 57 0 1
#> 146.1 24.00 0 63 1 0
#> 200.2 24.00 0 64 0 0
#> 65 24.00 0 57 1 0
#> 12.3 24.00 0 63 0 0
#> 118.2 24.00 0 44 1 0
#> 35.3 24.00 0 51 0 0
#> 67 24.00 0 25 0 0
#> 73.1 24.00 0 NA 0 1
#> 48.1 24.00 0 31 1 0
#> 9 24.00 0 31 1 0
#> 3.2 24.00 0 31 1 0
#> 94.1 24.00 0 51 0 1
#> 160 24.00 0 31 1 0
#> 73.2 24.00 0 NA 0 1
#> 83 24.00 0 6 0 0
#> 135 24.00 0 58 1 0
#> 87.1 24.00 0 27 0 0
#> 98.1 24.00 0 34 1 0
#> 74.1 24.00 0 43 0 1
#> 143 24.00 0 51 0 0
#> 64.2 24.00 0 43 0 0
#> 173.1 24.00 0 19 0 1
#> 193.1 24.00 0 45 0 1
#> 33 24.00 0 53 0 0
#> 44 24.00 0 56 0 0
#> 17 24.00 0 38 0 1
#> 67.1 24.00 0 25 0 0
#> 94.2 24.00 0 51 0 1
#> 27.2 24.00 0 63 1 0
#> 20.1 24.00 0 46 1 0
#> 160.1 24.00 0 31 1 0
#> 156 24.00 0 50 1 0
#> 67.2 24.00 0 25 0 0
#> 20.2 24.00 0 46 1 0
#> 19.1 24.00 0 57 0 1
#> 176 24.00 0 43 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.28 NA NA NA
#> 2 age, Cure model 0.0240 NA NA NA
#> 3 grade_ii, Cure model 0.184 NA NA NA
#> 4 grade_iii, Cure model 0.904 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00660 NA NA NA
#> 2 grade_ii, Survival model 0.572 NA NA NA
#> 3 grade_iii, Survival model 0.212 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.28143 0.02405 0.18375 0.90373
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 257.7
#> Residual Deviance: 246.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.28143339 0.02404753 0.18374711 0.90373168
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.006601053 0.571517716 0.212276511
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.084312697 0.674046007 0.990217335 0.882213521 0.901976213 0.055181216
#> [7] 0.142084626 0.842389254 0.644033640 0.394029249 0.583816039 0.693798168
#> [13] 0.433707458 0.463453786 0.674046007 0.654072625 0.201768992 0.006439579
#> [19] 0.473515932 0.483518247 0.812619227 0.414092553 0.693798168 0.654072625
#> [25] 0.443561094 0.523387621 0.162485943 0.573671142 0.623991737 0.182001909
#> [31] 0.265811976 0.265811976 0.503420807 0.065912759 0.822565001 0.633995526
#> [37] 0.294606407 0.247123015 0.792891012 0.201768992 0.294606407 0.533509341
#> [43] 0.941108786 0.733303335 0.024305208 0.980451920 0.713639446 0.324123111
#> [49] 0.483518247 0.911872063 0.162485943 0.383674383 0.324123111 0.713639446
#> [55] 0.733303335 0.065912759 0.247123015 0.503420807 0.753175320 0.191944358
#> [61] 0.113247427 0.553640441 0.882213521 0.792891012 0.201768992 0.024305208
#> [67] 0.024305208 0.872240831 0.201768992 0.960794982 0.593966489 0.533509341
#> [73] 0.324123111 0.394029249 0.006439579 0.852374904 0.113247427 0.094025100
#> [79] 0.613942593 0.553640441 0.132084908 0.314164935 0.941108786 0.911872063
#> [85] 0.414092553 0.373398595 0.152261566 0.911872063 0.284838562 0.103832881
#> [91] 0.782892175 0.024305208 0.970645981 0.772934928 0.852374904 0.324123111
#> [97] 0.753175320 0.593966489 0.201768992 0.822565001 0.363176388 0.453463541
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000
#>
#> $Time
#> 69 60 127 101 187 164 175 93 96 41 39 155 134
#> 23.23 13.15 3.53 9.97 9.92 23.60 21.91 10.33 14.54 18.02 15.59 13.08 17.81
#> 23 60.1 57 99 78 106 130 43 40 155.1 57.1 184 85
#> 16.92 13.15 14.46 21.19 23.88 16.67 16.47 12.10 18.00 13.08 14.46 17.77 16.44
#> 197 6 18 139 68 68.1 181 129 159 180 166 32 49
#> 21.60 15.64 15.21 21.49 20.62 20.62 16.46 23.41 10.55 14.82 19.98 20.90 12.19
#> 36 166.1 26 16 177 86 25 123 58 130.1 183 197.1 51
#> 21.19 19.98 15.77 8.71 12.53 23.81 6.32 13.00 19.34 16.47 9.24 21.60 18.23
#> 55 123.1 177.1 129.1 32.1 181.1 37 153 169 125 101.1 49.1 36.1
#> 19.34 13.00 12.53 23.41 20.90 16.46 12.52 21.33 22.41 15.65 9.97 12.19 21.19
#> 86.1 86.2 145 99.1 149 167 26.1 58.1 41.1 78.1 61 169.1 92
#> 23.81 23.81 10.07 21.19 8.37 15.55 15.77 19.34 18.02 23.88 10.12 22.41 22.92
#> 29 125.1 66 170 16.1 183.1 40.1 8 136 183.2 150 63 56
#> 15.45 15.65 22.13 19.54 8.71 9.24 18.00 18.43 21.83 9.24 20.33 22.77 12.21
#> 86.3 70 42 61.1 55.1 37.1 167.1 36.2 159.1 76 30 22 1
#> 23.81 7.38 12.43 10.12 19.34 12.52 15.55 21.19 10.55 19.22 17.43 24.00 24.00
#> 144 200 87 173 182 186 27 75 196 186.1 94 12 193
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 146 98 11 74 178 95 64 118 185 141 118.1 200.1 3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 121 35 82 48 12.1 144.1 174 80 35.1 47 7 27.1 71
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 198 82.1 20 186.2 109 12.2 35.2 3.1 64.1 19 146.1 200.2 65
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12.3 118.2 35.3 67 48.1 9 3.2 94.1 160 83 135 87.1 98.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 74.1 143 64.2 173.1 193.1 33 44 17 67.1 94.2 27.2 20.1 160.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156 67.2 20.2 19.1 176
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[32]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.003355093 0.189207693 0.123285876
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.99734623 0.02092983 0.10060029
#> grade_iii, Cure model
#> 0.48638691
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 81 14.06 1 34 0 0
#> 68 20.62 1 44 0 0
#> 6 15.64 1 39 0 0
#> 189 10.51 1 NA 1 0
#> 29 15.45 1 68 1 0
#> 39 15.59 1 37 0 1
#> 166 19.98 1 48 0 0
#> 106 16.67 1 49 1 0
#> 4 17.64 1 NA 0 1
#> 130 16.47 1 53 0 1
#> 91 5.33 1 61 0 1
#> 85 16.44 1 36 0 0
#> 136 21.83 1 43 0 1
#> 58 19.34 1 39 0 0
#> 125 15.65 1 67 1 0
#> 139 21.49 1 63 1 0
#> 134 17.81 1 47 1 0
#> 26 15.77 1 49 0 1
#> 179 18.63 1 42 0 0
#> 127 3.53 1 62 0 1
#> 175 21.91 1 43 0 0
#> 59 10.16 1 NA 1 0
#> 145 10.07 1 65 1 0
#> 91.1 5.33 1 61 0 1
#> 149 8.37 1 33 1 0
#> 63 22.77 1 31 1 0
#> 32 20.90 1 37 1 0
#> 134.1 17.81 1 47 1 0
#> 99 21.19 1 38 0 1
#> 149.1 8.37 1 33 1 0
#> 183 9.24 1 67 1 0
#> 177 12.53 1 75 0 0
#> 140 12.68 1 59 1 0
#> 145.1 10.07 1 65 1 0
#> 43 12.10 1 61 0 1
#> 79 16.23 1 54 1 0
#> 23 16.92 1 61 0 0
#> 45 17.42 1 54 0 1
#> 61 10.12 1 36 0 1
#> 92 22.92 1 47 0 1
#> 97 19.14 1 65 0 1
#> 66 22.13 1 53 0 0
#> 93 10.33 1 52 0 1
#> 199 19.81 1 NA 0 1
#> 181 16.46 1 45 0 1
#> 136.1 21.83 1 43 0 1
#> 68.1 20.62 1 44 0 0
#> 92.1 22.92 1 47 0 1
#> 107 11.18 1 54 1 0
#> 136.2 21.83 1 43 0 1
#> 88 18.37 1 47 0 0
#> 168 23.72 1 70 0 0
#> 97.1 19.14 1 65 0 1
#> 63.1 22.77 1 31 1 0
#> 45.1 17.42 1 54 0 1
#> 114 13.68 1 NA 0 0
#> 187 9.92 1 39 1 0
#> 184 17.77 1 38 0 0
#> 107.1 11.18 1 54 1 0
#> 5 16.43 1 51 0 1
#> 14 12.89 1 21 0 0
#> 133 14.65 1 57 0 0
#> 10 10.53 1 34 0 0
#> 171 16.57 1 41 0 1
#> 199.1 19.81 1 NA 0 1
#> 171.1 16.57 1 41 0 1
#> 111 17.45 1 47 0 1
#> 16 8.71 1 71 0 1
#> 129 23.41 1 53 1 0
#> 181.1 16.46 1 45 0 1
#> 190 20.81 1 42 1 0
#> 111.1 17.45 1 47 0 1
#> 125.1 15.65 1 67 1 0
#> 177.1 12.53 1 75 0 0
#> 29.1 15.45 1 68 1 0
#> 105 19.75 1 60 0 0
#> 134.2 17.81 1 47 1 0
#> 158 20.14 1 74 1 0
#> 136.3 21.83 1 43 0 1
#> 157 15.10 1 47 0 0
#> 39.1 15.59 1 37 0 1
#> 14.1 12.89 1 21 0 0
#> 45.2 17.42 1 54 0 1
#> 68.2 20.62 1 44 0 0
#> 140.1 12.68 1 59 1 0
#> 133.1 14.65 1 57 0 0
#> 29.2 15.45 1 68 1 0
#> 111.2 17.45 1 47 0 1
#> 92.2 22.92 1 47 0 1
#> 155 13.08 1 26 0 0
#> 181.2 16.46 1 45 0 1
#> 66.1 22.13 1 53 0 0
#> 4.1 17.64 1 NA 0 1
#> 170 19.54 1 43 0 1
#> 157.1 15.10 1 47 0 0
#> 88.1 18.37 1 47 0 0
#> 155.1 13.08 1 26 0 0
#> 66.2 22.13 1 53 0 0
#> 93.1 10.33 1 52 0 1
#> 77 7.27 1 67 0 1
#> 188 16.16 1 46 0 1
#> 149.2 8.37 1 33 1 0
#> 134.3 17.81 1 47 1 0
#> 155.2 13.08 1 26 0 0
#> 66.3 22.13 1 53 0 0
#> 14.2 12.89 1 21 0 0
#> 139.1 21.49 1 63 1 0
#> 77.1 7.27 1 67 0 1
#> 181.3 16.46 1 45 0 1
#> 177.2 12.53 1 75 0 0
#> 134.4 17.81 1 47 1 0
#> 154 12.63 1 20 1 0
#> 7 24.00 0 37 1 0
#> 173 24.00 0 19 0 1
#> 2 24.00 0 9 0 0
#> 109 24.00 0 48 0 0
#> 9 24.00 0 31 1 0
#> 35 24.00 0 51 0 0
#> 146 24.00 0 63 1 0
#> 151 24.00 0 42 0 0
#> 82 24.00 0 34 0 0
#> 112 24.00 0 61 0 0
#> 47 24.00 0 38 0 1
#> 191 24.00 0 60 0 1
#> 33 24.00 0 53 0 0
#> 67 24.00 0 25 0 0
#> 31 24.00 0 36 0 1
#> 22 24.00 0 52 1 0
#> 7.1 24.00 0 37 1 0
#> 54 24.00 0 53 1 0
#> 178 24.00 0 52 1 0
#> 146.1 24.00 0 63 1 0
#> 12 24.00 0 63 0 0
#> 104 24.00 0 50 1 0
#> 1 24.00 0 23 1 0
#> 198 24.00 0 66 0 1
#> 83 24.00 0 6 0 0
#> 64 24.00 0 43 0 0
#> 19 24.00 0 57 0 1
#> 74 24.00 0 43 0 1
#> 148 24.00 0 61 1 0
#> 74.1 24.00 0 43 0 1
#> 109.1 24.00 0 48 0 0
#> 80 24.00 0 41 0 0
#> 156 24.00 0 50 1 0
#> 38 24.00 0 31 1 0
#> 94 24.00 0 51 0 1
#> 28 24.00 0 67 1 0
#> 11 24.00 0 42 0 1
#> 118 24.00 0 44 1 0
#> 144 24.00 0 28 0 1
#> 191.1 24.00 0 60 0 1
#> 163 24.00 0 66 0 0
#> 146.2 24.00 0 63 1 0
#> 135 24.00 0 58 1 0
#> 132 24.00 0 55 0 0
#> 65 24.00 0 57 1 0
#> 17 24.00 0 38 0 1
#> 165 24.00 0 47 0 0
#> 162 24.00 0 51 0 0
#> 98 24.00 0 34 1 0
#> 182 24.00 0 35 0 0
#> 54.1 24.00 0 53 1 0
#> 87 24.00 0 27 0 0
#> 148.1 24.00 0 61 1 0
#> 64.1 24.00 0 43 0 0
#> 122 24.00 0 66 0 0
#> 94.1 24.00 0 51 0 1
#> 83.1 24.00 0 6 0 0
#> 193 24.00 0 45 0 1
#> 84 24.00 0 39 0 1
#> 82.1 24.00 0 34 0 0
#> 152 24.00 0 36 0 1
#> 64.2 24.00 0 43 0 0
#> 47.1 24.00 0 38 0 1
#> 87.1 24.00 0 27 0 0
#> 1.1 24.00 0 23 1 0
#> 7.2 24.00 0 37 1 0
#> 48 24.00 0 31 1 0
#> 148.2 24.00 0 61 1 0
#> 198.1 24.00 0 66 0 1
#> 112.1 24.00 0 61 0 0
#> 72 24.00 0 40 0 1
#> 122.1 24.00 0 66 0 0
#> 38.1 24.00 0 31 1 0
#> 94.2 24.00 0 51 0 1
#> 72.1 24.00 0 40 0 1
#> 44 24.00 0 56 0 0
#> 182.1 24.00 0 35 0 0
#> 178.1 24.00 0 52 1 0
#> 2.1 24.00 0 9 0 0
#> 12.1 24.00 0 63 0 0
#> 98.1 24.00 0 34 1 0
#> 102 24.00 0 49 0 0
#> 126 24.00 0 48 0 0
#> 21 24.00 0 47 0 0
#> 173.1 24.00 0 19 0 1
#> 191.2 24.00 0 60 0 1
#> 131 24.00 0 66 0 0
#> 132.1 24.00 0 55 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.997 NA NA NA
#> 2 age, Cure model 0.0209 NA NA NA
#> 3 grade_ii, Cure model 0.101 NA NA NA
#> 4 grade_iii, Cure model 0.486 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00336 NA NA NA
#> 2 grade_ii, Survival model 0.189 NA NA NA
#> 3 grade_iii, Survival model 0.123 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.99735 0.02093 0.10060 0.48639
#>
#> Degrees of Freedom: 192 Total (i.e. Null); 189 Residual
#> Null Deviance: 266.1
#> Residual Deviance: 259.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.99734623 0.02092983 0.10060029 0.48638691
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.003355093 0.189207693 0.123285876
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.75106581 0.30019014 0.67151886 0.69585565 0.67970011 0.34096849
#> [7] 0.54542806 0.57146261 0.97833909 0.61332625 0.20226833 0.37150681
#> [13] 0.65522845 0.24579377 0.43004507 0.64692546 0.40101293 0.99277588
#> [19] 0.18946813 0.90482899 0.97833909 0.94198506 0.11532484 0.27863402
#> [25] 0.43004507 0.26761966 0.94198506 0.92716866 0.82893930 0.80568730
#> [31] 0.90482899 0.85182264 0.63021314 0.53658933 0.51041122 0.89729147
#> [37] 0.07360750 0.38156775 0.14278815 0.88224494 0.58011060 0.20226833
#> [43] 0.30019014 0.07360750 0.85949286 0.20226833 0.41081991 0.02307637
#> [49] 0.38156775 0.11532484 0.51041122 0.91971708 0.47452223 0.85949286
#> [55] 0.62178932 0.78235167 0.73533027 0.87464418 0.55420645 0.55420645
#> [61] 0.48374681 0.93458964 0.05088119 0.58011060 0.28949052 0.48374681
#> [67] 0.65522845 0.82893930 0.69585565 0.35122122 0.43004507 0.33066164
#> [73] 0.20226833 0.71952346 0.67970011 0.78235167 0.51041122 0.30019014
#> [79] 0.80568730 0.73533027 0.69585565 0.48374681 0.07360750 0.75896518
#> [85] 0.58011060 0.14278815 0.36140767 0.71952346 0.41081991 0.75896518
#> [91] 0.14278815 0.88224494 0.96381915 0.63858680 0.94198506 0.43004507
#> [97] 0.75896518 0.14278815 0.78235167 0.24579377 0.96381915 0.58011060
#> [103] 0.82893930 0.43004507 0.82117837 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [193] 0.00000000
#>
#> $Time
#> 81 68 6 29 39 166 106 130 91 85 136 58 125
#> 14.06 20.62 15.64 15.45 15.59 19.98 16.67 16.47 5.33 16.44 21.83 19.34 15.65
#> 139 134 26 179 127 175 145 91.1 149 63 32 134.1 99
#> 21.49 17.81 15.77 18.63 3.53 21.91 10.07 5.33 8.37 22.77 20.90 17.81 21.19
#> 149.1 183 177 140 145.1 43 79 23 45 61 92 97 66
#> 8.37 9.24 12.53 12.68 10.07 12.10 16.23 16.92 17.42 10.12 22.92 19.14 22.13
#> 93 181 136.1 68.1 92.1 107 136.2 88 168 97.1 63.1 45.1 187
#> 10.33 16.46 21.83 20.62 22.92 11.18 21.83 18.37 23.72 19.14 22.77 17.42 9.92
#> 184 107.1 5 14 133 10 171 171.1 111 16 129 181.1 190
#> 17.77 11.18 16.43 12.89 14.65 10.53 16.57 16.57 17.45 8.71 23.41 16.46 20.81
#> 111.1 125.1 177.1 29.1 105 134.2 158 136.3 157 39.1 14.1 45.2 68.2
#> 17.45 15.65 12.53 15.45 19.75 17.81 20.14 21.83 15.10 15.59 12.89 17.42 20.62
#> 140.1 133.1 29.2 111.2 92.2 155 181.2 66.1 170 157.1 88.1 155.1 66.2
#> 12.68 14.65 15.45 17.45 22.92 13.08 16.46 22.13 19.54 15.10 18.37 13.08 22.13
#> 93.1 77 188 149.2 134.3 155.2 66.3 14.2 139.1 77.1 181.3 177.2 134.4
#> 10.33 7.27 16.16 8.37 17.81 13.08 22.13 12.89 21.49 7.27 16.46 12.53 17.81
#> 154 7 173 2 109 9 35 146 151 82 112 47 191
#> 12.63 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33 67 31 22 7.1 54 178 146.1 12 104 1 198 83
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64 19 74 148 74.1 109.1 80 156 38 94 28 11 118
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 144 191.1 163 146.2 135 132 65 17 165 162 98 182 54.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87 148.1 64.1 122 94.1 83.1 193 84 82.1 152 64.2 47.1 87.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1.1 7.2 48 148.2 198.1 112.1 72 122.1 38.1 94.2 72.1 44 182.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178.1 2.1 12.1 98.1 102 126 21 173.1 191.2 131 132.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[33]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.008552316 0.660286231 0.198011963
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.290840325 0.009103947 -0.138597711
#> grade_iii, Cure model
#> 0.341322465
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 39 15.59 1 37 0 1
#> 85 16.44 1 36 0 0
#> 197 21.60 1 69 1 0
#> 183 9.24 1 67 1 0
#> 81 14.06 1 34 0 0
#> 105 19.75 1 60 0 0
#> 167 15.55 1 56 1 0
#> 97 19.14 1 65 0 1
#> 63 22.77 1 31 1 0
#> 32 20.90 1 37 1 0
#> 76 19.22 1 54 0 1
#> 183.1 9.24 1 67 1 0
#> 85.1 16.44 1 36 0 0
#> 97.1 19.14 1 65 0 1
#> 181 16.46 1 45 0 1
#> 30 17.43 1 78 0 0
#> 175 21.91 1 43 0 0
#> 51 18.23 1 83 0 1
#> 187 9.92 1 39 1 0
#> 79 16.23 1 54 1 0
#> 36 21.19 1 48 0 1
#> 107 11.18 1 54 1 0
#> 14 12.89 1 21 0 0
#> 30.1 17.43 1 78 0 0
#> 159 10.55 1 50 0 1
#> 78 23.88 1 43 0 0
#> 88 18.37 1 47 0 0
#> 15 22.68 1 48 0 0
#> 199 19.81 1 NA 0 1
#> 85.2 16.44 1 36 0 0
#> 179 18.63 1 42 0 0
#> 86 23.81 1 58 0 1
#> 179.1 18.63 1 42 0 0
#> 197.1 21.60 1 69 1 0
#> 150 20.33 1 48 0 0
#> 30.2 17.43 1 78 0 0
#> 194 22.40 1 38 0 1
#> 79.1 16.23 1 54 1 0
#> 32.1 20.90 1 37 1 0
#> 195 11.76 1 NA 1 0
#> 180 14.82 1 37 0 0
#> 188 16.16 1 46 0 1
#> 164 23.60 1 76 0 1
#> 58 19.34 1 39 0 0
#> 129 23.41 1 53 1 0
#> 10 10.53 1 34 0 0
#> 155 13.08 1 26 0 0
#> 81.1 14.06 1 34 0 0
#> 168 23.72 1 70 0 0
#> 127 3.53 1 62 0 1
#> 128 20.35 1 35 0 1
#> 6 15.64 1 39 0 0
#> 194.1 22.40 1 38 0 1
#> 49 12.19 1 48 1 0
#> 36.1 21.19 1 48 0 1
#> 110 17.56 1 65 0 1
#> 29 15.45 1 68 1 0
#> 106 16.67 1 49 1 0
#> 155.1 13.08 1 26 0 0
#> 164.1 23.60 1 76 0 1
#> 158 20.14 1 74 1 0
#> 136 21.83 1 43 0 1
#> 39.1 15.59 1 37 0 1
#> 123 13.00 1 44 1 0
#> 61 10.12 1 36 0 1
#> 154 12.63 1 20 1 0
#> 78.1 23.88 1 43 0 0
#> 8 18.43 1 32 0 0
#> 29.1 15.45 1 68 1 0
#> 177 12.53 1 75 0 0
#> 101 9.97 1 10 0 1
#> 99 21.19 1 38 0 1
#> 5 16.43 1 51 0 1
#> 40 18.00 1 28 1 0
#> 155.2 13.08 1 26 0 0
#> 189 10.51 1 NA 1 0
#> 125 15.65 1 67 1 0
#> 92 22.92 1 47 0 1
#> 49.1 12.19 1 48 1 0
#> 170 19.54 1 43 0 1
#> 18 15.21 1 49 1 0
#> 89 11.44 1 NA 0 0
#> 96 14.54 1 33 0 1
#> 114 13.68 1 NA 0 0
#> 69 23.23 1 25 0 1
#> 169 22.41 1 46 0 0
#> 100 16.07 1 60 0 0
#> 78.2 23.88 1 43 0 0
#> 70 7.38 1 30 1 0
#> 69.1 23.23 1 25 0 1
#> 123.1 13.00 1 44 1 0
#> 127.1 3.53 1 62 0 1
#> 171 16.57 1 41 0 1
#> 5.1 16.43 1 51 0 1
#> 39.2 15.59 1 37 0 1
#> 101.1 9.97 1 10 0 1
#> 127.2 3.53 1 62 0 1
#> 45 17.42 1 54 0 1
#> 8.1 18.43 1 32 0 0
#> 49.2 12.19 1 48 1 0
#> 136.1 21.83 1 43 0 1
#> 197.2 21.60 1 69 1 0
#> 8.2 18.43 1 32 0 0
#> 127.3 3.53 1 62 0 1
#> 91 5.33 1 61 0 1
#> 157 15.10 1 47 0 0
#> 86.1 23.81 1 58 0 1
#> 78.3 23.88 1 43 0 0
#> 154.1 12.63 1 20 1 0
#> 181.1 16.46 1 45 0 1
#> 43 12.10 1 61 0 1
#> 199.1 19.81 1 NA 0 1
#> 53 24.00 0 32 0 1
#> 191 24.00 0 60 0 1
#> 82 24.00 0 34 0 0
#> 143 24.00 0 51 0 0
#> 44 24.00 0 56 0 0
#> 126 24.00 0 48 0 0
#> 64 24.00 0 43 0 0
#> 71 24.00 0 51 0 0
#> 143.1 24.00 0 51 0 0
#> 103 24.00 0 56 1 0
#> 146 24.00 0 63 1 0
#> 118 24.00 0 44 1 0
#> 2 24.00 0 9 0 0
#> 172 24.00 0 41 0 0
#> 115 24.00 0 NA 1 0
#> 3 24.00 0 31 1 0
#> 21 24.00 0 47 0 0
#> 1 24.00 0 23 1 0
#> 161 24.00 0 45 0 0
#> 54 24.00 0 53 1 0
#> 196 24.00 0 19 0 0
#> 126.1 24.00 0 48 0 0
#> 131 24.00 0 66 0 0
#> 143.2 24.00 0 51 0 0
#> 46 24.00 0 71 0 0
#> 152 24.00 0 36 0 1
#> 33 24.00 0 53 0 0
#> 147 24.00 0 76 1 0
#> 186 24.00 0 45 1 0
#> 72 24.00 0 40 0 1
#> 84 24.00 0 39 0 1
#> 94 24.00 0 51 0 1
#> 172.1 24.00 0 41 0 0
#> 17 24.00 0 38 0 1
#> 22 24.00 0 52 1 0
#> 38 24.00 0 31 1 0
#> 80 24.00 0 41 0 0
#> 12 24.00 0 63 0 0
#> 94.1 24.00 0 51 0 1
#> 80.1 24.00 0 41 0 0
#> 148 24.00 0 61 1 0
#> 193 24.00 0 45 0 1
#> 186.1 24.00 0 45 1 0
#> 75 24.00 0 21 1 0
#> 115.1 24.00 0 NA 1 0
#> 74 24.00 0 43 0 1
#> 119 24.00 0 17 0 0
#> 186.2 24.00 0 45 1 0
#> 17.1 24.00 0 38 0 1
#> 182 24.00 0 35 0 0
#> 47 24.00 0 38 0 1
#> 116 24.00 0 58 0 1
#> 103.1 24.00 0 56 1 0
#> 7 24.00 0 37 1 0
#> 72.1 24.00 0 40 0 1
#> 162 24.00 0 51 0 0
#> 198 24.00 0 66 0 1
#> 9 24.00 0 31 1 0
#> 1.1 24.00 0 23 1 0
#> 173 24.00 0 19 0 1
#> 20 24.00 0 46 1 0
#> 46.1 24.00 0 71 0 0
#> 74.1 24.00 0 43 0 1
#> 200 24.00 0 64 0 0
#> 98 24.00 0 34 1 0
#> 174 24.00 0 49 1 0
#> 80.2 24.00 0 41 0 0
#> 20.1 24.00 0 46 1 0
#> 48 24.00 0 31 1 0
#> 116.1 24.00 0 58 0 1
#> 95 24.00 0 68 0 1
#> 3.1 24.00 0 31 1 0
#> 116.2 24.00 0 58 0 1
#> 120 24.00 0 68 0 1
#> 67 24.00 0 25 0 0
#> 17.2 24.00 0 38 0 1
#> 12.1 24.00 0 63 0 0
#> 163 24.00 0 66 0 0
#> 174.1 24.00 0 49 1 0
#> 53.1 24.00 0 32 0 1
#> 74.2 24.00 0 43 0 1
#> 141 24.00 0 44 1 0
#> 34 24.00 0 36 0 0
#> 186.3 24.00 0 45 1 0
#> 147.1 24.00 0 76 1 0
#> 74.3 24.00 0 43 0 1
#> 3.2 24.00 0 31 1 0
#> 94.2 24.00 0 51 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.291 NA NA NA
#> 2 age, Cure model 0.00910 NA NA NA
#> 3 grade_ii, Cure model -0.139 NA NA NA
#> 4 grade_iii, Cure model 0.341 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00855 NA NA NA
#> 2 grade_ii, Survival model 0.660 NA NA NA
#> 3 grade_iii, Survival model 0.198 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.290840 0.009104 -0.138598 0.341322
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.1
#> Residual Deviance: 261.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.290840325 0.009103947 -0.138597711 0.341322465
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.008552316 0.660286231 0.198011963
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.583781842 0.470635526 0.157341695 0.917592085 0.688009422 0.251224848
#> [7] 0.614831226 0.287130321 0.089499458 0.208127945 0.278048399 0.917592085
#> [13] 0.470635526 0.287130321 0.450516709 0.390729978 0.131114714 0.361573400
#> [19] 0.907209881 0.521631405 0.182436686 0.844765302 0.761738602 0.390729978
#> [25] 0.855153685 0.004906709 0.351895492 0.097575554 0.470635526 0.305348401
#> [31] 0.020802720 0.305348401 0.157341695 0.233702334 0.390729978 0.114409122
#> [37] 0.521631405 0.208127945 0.666965176 0.542085554 0.040995009 0.269034767
#> [43] 0.056974997 0.865568025 0.709067160 0.688009422 0.033290071 0.958833700
#> [49] 0.225046036 0.573306427 0.114409122 0.803592658 0.182436686 0.381006045
#> [55] 0.625324576 0.430356371 0.709067160 0.040995009 0.242467973 0.139930862
#> [61] 0.583781842 0.740697086 0.876014078 0.772357315 0.004906709 0.323900735
#> [67] 0.625324576 0.793091490 0.886473109 0.182436686 0.500999787 0.371356214
#> [73] 0.709067160 0.562885022 0.081054878 0.803592658 0.260105998 0.646078686
#> [79] 0.677480698 0.065332247 0.105883433 0.552445996 0.004906709 0.938196760
#> [85] 0.065332247 0.740697086 0.958833700 0.440420207 0.500999787 0.583781842
#> [91] 0.886473109 0.958833700 0.420227935 0.323900735 0.803592658 0.139930862
#> [97] 0.157341695 0.323900735 0.958833700 0.948499710 0.656494437 0.020802720
#> [103] 0.004906709 0.772357315 0.450516709 0.834348800 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 39 85 197 183 81 105 167 97 63 32 76 183.1 85.1
#> 15.59 16.44 21.60 9.24 14.06 19.75 15.55 19.14 22.77 20.90 19.22 9.24 16.44
#> 97.1 181 30 175 51 187 79 36 107 14 30.1 159 78
#> 19.14 16.46 17.43 21.91 18.23 9.92 16.23 21.19 11.18 12.89 17.43 10.55 23.88
#> 88 15 85.2 179 86 179.1 197.1 150 30.2 194 79.1 32.1 180
#> 18.37 22.68 16.44 18.63 23.81 18.63 21.60 20.33 17.43 22.40 16.23 20.90 14.82
#> 188 164 58 129 10 155 81.1 168 127 128 6 194.1 49
#> 16.16 23.60 19.34 23.41 10.53 13.08 14.06 23.72 3.53 20.35 15.64 22.40 12.19
#> 36.1 110 29 106 155.1 164.1 158 136 39.1 123 61 154 78.1
#> 21.19 17.56 15.45 16.67 13.08 23.60 20.14 21.83 15.59 13.00 10.12 12.63 23.88
#> 8 29.1 177 101 99 5 40 155.2 125 92 49.1 170 18
#> 18.43 15.45 12.53 9.97 21.19 16.43 18.00 13.08 15.65 22.92 12.19 19.54 15.21
#> 96 69 169 100 78.2 70 69.1 123.1 127.1 171 5.1 39.2 101.1
#> 14.54 23.23 22.41 16.07 23.88 7.38 23.23 13.00 3.53 16.57 16.43 15.59 9.97
#> 127.2 45 8.1 49.2 136.1 197.2 8.2 127.3 91 157 86.1 78.3 154.1
#> 3.53 17.42 18.43 12.19 21.83 21.60 18.43 3.53 5.33 15.10 23.81 23.88 12.63
#> 181.1 43 53 191 82 143 44 126 64 71 143.1 103 146
#> 16.46 12.10 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 118 2 172 3 21 1 161 54 196 126.1 131 143.2 46
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152 33 147 186 72 84 94 172.1 17 22 38 80 12
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94.1 80.1 148 193 186.1 75 74 119 186.2 17.1 182 47 116
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103.1 7 72.1 162 198 9 1.1 173 20 46.1 74.1 200 98
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174 80.2 20.1 48 116.1 95 3.1 116.2 120 67 17.2 12.1 163
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174.1 53.1 74.2 141 34 186.3 147.1 74.3 3.2 94.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[34]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.003941422 0.100580834 0.249660458
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.329755267 0.001358785 0.165656520
#> grade_iii, Cure model
#> 1.001553117
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 149 8.37 1 33 1 0
#> 113 22.86 1 34 0 0
#> 56 12.21 1 60 0 0
#> 101 9.97 1 10 0 1
#> 190 20.81 1 42 1 0
#> 14 12.89 1 21 0 0
#> 42 12.43 1 49 0 1
#> 56.1 12.21 1 60 0 0
#> 76 19.22 1 54 0 1
#> 158 20.14 1 74 1 0
#> 50 10.02 1 NA 1 0
#> 86 23.81 1 58 0 1
#> 49 12.19 1 48 1 0
#> 155 13.08 1 26 0 0
#> 153 21.33 1 55 1 0
#> 129 23.41 1 53 1 0
#> 110 17.56 1 65 0 1
#> 192 16.44 1 31 1 0
#> 130 16.47 1 53 0 1
#> 85 16.44 1 36 0 0
#> 89 11.44 1 NA 0 0
#> 192.1 16.44 1 31 1 0
#> 192.2 16.44 1 31 1 0
#> 76.1 19.22 1 54 0 1
#> 195 11.76 1 NA 1 0
#> 50.1 10.02 1 NA 1 0
#> 85.1 16.44 1 36 0 0
#> 110.1 17.56 1 65 0 1
#> 177 12.53 1 75 0 0
#> 59 10.16 1 NA 1 0
#> 128 20.35 1 35 0 1
#> 180 14.82 1 37 0 0
#> 30 17.43 1 78 0 0
#> 188 16.16 1 46 0 1
#> 93 10.33 1 52 0 1
#> 101.1 9.97 1 10 0 1
#> 16 8.71 1 71 0 1
#> 139 21.49 1 63 1 0
#> 170 19.54 1 43 0 1
#> 169 22.41 1 46 0 0
#> 42.1 12.43 1 49 0 1
#> 39 15.59 1 37 0 1
#> 194 22.40 1 38 0 1
#> 52 10.42 1 52 0 1
#> 179 18.63 1 42 0 0
#> 197 21.60 1 69 1 0
#> 184 17.77 1 38 0 0
#> 63 22.77 1 31 1 0
#> 57 14.46 1 45 0 1
#> 97 19.14 1 65 0 1
#> 93.1 10.33 1 52 0 1
#> 32 20.90 1 37 1 0
#> 181 16.46 1 45 0 1
#> 111 17.45 1 47 0 1
#> 49.1 12.19 1 48 1 0
#> 108 18.29 1 39 0 1
#> 145 10.07 1 65 1 0
#> 90 20.94 1 50 0 1
#> 85.2 16.44 1 36 0 0
#> 194.1 22.40 1 38 0 1
#> 189 10.51 1 NA 1 0
#> 55 19.34 1 69 0 1
#> 136 21.83 1 43 0 1
#> 88 18.37 1 47 0 0
#> 189.1 10.51 1 NA 1 0
#> 79 16.23 1 54 1 0
#> 197.1 21.60 1 69 1 0
#> 57.1 14.46 1 45 0 1
#> 134 17.81 1 47 1 0
#> 13 14.34 1 54 0 1
#> 105 19.75 1 60 0 0
#> 183 9.24 1 67 1 0
#> 42.2 12.43 1 49 0 1
#> 93.2 10.33 1 52 0 1
#> 159 10.55 1 50 0 1
#> 30.1 17.43 1 78 0 0
#> 130.1 16.47 1 53 0 1
#> 79.1 16.23 1 54 1 0
#> 93.3 10.33 1 52 0 1
#> 99 21.19 1 38 0 1
#> 14.1 12.89 1 21 0 0
#> 110.2 17.56 1 65 0 1
#> 183.1 9.24 1 67 1 0
#> 166 19.98 1 48 0 0
#> 128.1 20.35 1 35 0 1
#> 195.1 11.76 1 NA 1 0
#> 42.3 12.43 1 49 0 1
#> 60 13.15 1 38 1 0
#> 188.1 16.16 1 46 0 1
#> 189.2 10.51 1 NA 1 0
#> 145.1 10.07 1 65 1 0
#> 66 22.13 1 53 0 0
#> 101.2 9.97 1 10 0 1
#> 90.1 20.94 1 50 0 1
#> 183.2 9.24 1 67 1 0
#> 29 15.45 1 68 1 0
#> 49.2 12.19 1 48 1 0
#> 23 16.92 1 61 0 0
#> 60.1 13.15 1 38 1 0
#> 32.1 20.90 1 37 1 0
#> 157 15.10 1 47 0 0
#> 99.1 21.19 1 38 0 1
#> 63.1 22.77 1 31 1 0
#> 24 23.89 1 38 0 0
#> 90.2 20.94 1 50 0 1
#> 101.3 9.97 1 10 0 1
#> 128.2 20.35 1 35 0 1
#> 61 10.12 1 36 0 1
#> 43 12.10 1 61 0 1
#> 77 7.27 1 67 0 1
#> 18 15.21 1 49 1 0
#> 99.2 21.19 1 38 0 1
#> 165 24.00 0 47 0 0
#> 94 24.00 0 51 0 1
#> 131 24.00 0 66 0 0
#> 20 24.00 0 46 1 0
#> 152 24.00 0 36 0 1
#> 31 24.00 0 36 0 1
#> 98 24.00 0 34 1 0
#> 143 24.00 0 51 0 0
#> 17 24.00 0 38 0 1
#> 3 24.00 0 31 1 0
#> 102 24.00 0 49 0 0
#> 161 24.00 0 45 0 0
#> 17.1 24.00 0 38 0 1
#> 156 24.00 0 50 1 0
#> 172 24.00 0 41 0 0
#> 21 24.00 0 47 0 0
#> 121 24.00 0 57 1 0
#> 98.1 24.00 0 34 1 0
#> 19 24.00 0 57 0 1
#> 27 24.00 0 63 1 0
#> 22 24.00 0 52 1 0
#> 119 24.00 0 17 0 0
#> 20.1 24.00 0 46 1 0
#> 161.1 24.00 0 45 0 0
#> 27.1 24.00 0 63 1 0
#> 182 24.00 0 35 0 0
#> 160 24.00 0 31 1 0
#> 12 24.00 0 63 0 0
#> 121.1 24.00 0 57 1 0
#> 28 24.00 0 67 1 0
#> 2 24.00 0 9 0 0
#> 53 24.00 0 32 0 1
#> 172.1 24.00 0 41 0 0
#> 196 24.00 0 19 0 0
#> 122 24.00 0 66 0 0
#> 84 24.00 0 39 0 1
#> 115 24.00 0 NA 1 0
#> 152.1 24.00 0 36 0 1
#> 135 24.00 0 58 1 0
#> 27.2 24.00 0 63 1 0
#> 27.3 24.00 0 63 1 0
#> 116 24.00 0 58 0 1
#> 12.1 24.00 0 63 0 0
#> 95 24.00 0 68 0 1
#> 22.1 24.00 0 52 1 0
#> 12.2 24.00 0 63 0 0
#> 53.1 24.00 0 32 0 1
#> 138 24.00 0 44 1 0
#> 147 24.00 0 76 1 0
#> 9 24.00 0 31 1 0
#> 198 24.00 0 66 0 1
#> 98.2 24.00 0 34 1 0
#> 142 24.00 0 53 0 0
#> 160.1 24.00 0 31 1 0
#> 28.1 24.00 0 67 1 0
#> 84.1 24.00 0 39 0 1
#> 102.1 24.00 0 49 0 0
#> 193 24.00 0 45 0 1
#> 84.2 24.00 0 39 0 1
#> 147.1 24.00 0 76 1 0
#> 178 24.00 0 52 1 0
#> 94.1 24.00 0 51 0 1
#> 84.3 24.00 0 39 0 1
#> 174 24.00 0 49 1 0
#> 109 24.00 0 48 0 0
#> 148 24.00 0 61 1 0
#> 48 24.00 0 31 1 0
#> 185 24.00 0 44 1 0
#> 17.2 24.00 0 38 0 1
#> 122.1 24.00 0 66 0 0
#> 74 24.00 0 43 0 1
#> 33 24.00 0 53 0 0
#> 44 24.00 0 56 0 0
#> 62 24.00 0 71 0 0
#> 146 24.00 0 63 1 0
#> 174.1 24.00 0 49 1 0
#> 53.2 24.00 0 32 0 1
#> 122.2 24.00 0 66 0 0
#> 22.2 24.00 0 52 1 0
#> 94.2 24.00 0 51 0 1
#> 163 24.00 0 66 0 0
#> 126 24.00 0 48 0 0
#> 143.1 24.00 0 51 0 0
#> 95.1 24.00 0 68 0 1
#> 22.3 24.00 0 52 1 0
#> 196.1 24.00 0 19 0 0
#> 72 24.00 0 40 0 1
#> 83 24.00 0 6 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.330 NA NA NA
#> 2 age, Cure model 0.00136 NA NA NA
#> 3 grade_ii, Cure model 0.166 NA NA NA
#> 4 grade_iii, Cure model 1.00 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00394 NA NA NA
#> 2 grade_ii, Survival model 0.101 NA NA NA
#> 3 grade_iii, Survival model 0.250 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.329755 0.001359 0.165657 1.001553
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 262
#> Residual Deviance: 253 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.329755267 0.001358785 0.165656520 1.001553117
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.003941422 0.100580834 0.249660458
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.98626008 0.08991711 0.82270762 0.93101467 0.35319256 0.77012537
#> [7] 0.79310577 0.82270762 0.44384456 0.39393058 0.04924553 0.83757214
#> [13] 0.76241746 0.25308676 0.07061196 0.51818784 0.60392350 0.57872912
#> [19] 0.60392350 0.60392350 0.60392350 0.44384456 0.60392350 0.51818784
#> [25] 0.78543774 0.36391606 0.71585797 0.55296662 0.66802574 0.88154057
#> [31] 0.93101467 0.97936166 0.24013348 0.42418979 0.14051540 0.79310577
#> [37] 0.68403523 0.15706986 0.87425338 0.47202706 0.21436182 0.50905255
#> [43] 0.10866263 0.72376072 0.46265235 0.88154057 0.33187693 0.59552767
#> [49] 0.54422319 0.83757214 0.49067296 0.91692037 0.29985837 0.60392350
#> [55] 0.15706986 0.43409333 0.20027704 0.48136838 0.65180689 0.21436182
#> [61] 0.72376072 0.49989070 0.73930015 0.41416440 0.95871103 0.79310577
#> [67] 0.88154057 0.86693107 0.55296662 0.57872912 0.65180689 0.88154057
#> [73] 0.26579726 0.77012537 0.51818784 0.95871103 0.40407386 0.36391606
#> [79] 0.79310577 0.74706291 0.66802574 0.91692037 0.18565762 0.93101467
#> [85] 0.29985837 0.95871103 0.69204164 0.83757214 0.57012159 0.74706291
#> [91] 0.33187693 0.70794151 0.26579726 0.10866263 0.02082004 0.29985837
#> [97] 0.93101467 0.36391606 0.90979881 0.85957377 0.99314599 0.70000699
#> [103] 0.26579726 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 149 113 56 101 190 14 42 56.1 76 158 86 49 155
#> 8.37 22.86 12.21 9.97 20.81 12.89 12.43 12.21 19.22 20.14 23.81 12.19 13.08
#> 153 129 110 192 130 85 192.1 192.2 76.1 85.1 110.1 177 128
#> 21.33 23.41 17.56 16.44 16.47 16.44 16.44 16.44 19.22 16.44 17.56 12.53 20.35
#> 180 30 188 93 101.1 16 139 170 169 42.1 39 194 52
#> 14.82 17.43 16.16 10.33 9.97 8.71 21.49 19.54 22.41 12.43 15.59 22.40 10.42
#> 179 197 184 63 57 97 93.1 32 181 111 49.1 108 145
#> 18.63 21.60 17.77 22.77 14.46 19.14 10.33 20.90 16.46 17.45 12.19 18.29 10.07
#> 90 85.2 194.1 55 136 88 79 197.1 57.1 134 13 105 183
#> 20.94 16.44 22.40 19.34 21.83 18.37 16.23 21.60 14.46 17.81 14.34 19.75 9.24
#> 42.2 93.2 159 30.1 130.1 79.1 93.3 99 14.1 110.2 183.1 166 128.1
#> 12.43 10.33 10.55 17.43 16.47 16.23 10.33 21.19 12.89 17.56 9.24 19.98 20.35
#> 42.3 60 188.1 145.1 66 101.2 90.1 183.2 29 49.2 23 60.1 32.1
#> 12.43 13.15 16.16 10.07 22.13 9.97 20.94 9.24 15.45 12.19 16.92 13.15 20.90
#> 157 99.1 63.1 24 90.2 101.3 128.2 61 43 77 18 99.2 165
#> 15.10 21.19 22.77 23.89 20.94 9.97 20.35 10.12 12.10 7.27 15.21 21.19 24.00
#> 94 131 20 152 31 98 143 17 3 102 161 17.1 156
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172 21 121 98.1 19 27 22 119 20.1 161.1 27.1 182 160
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12 121.1 28 2 53 172.1 196 122 84 152.1 135 27.2 27.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116 12.1 95 22.1 12.2 53.1 138 147 9 198 98.2 142 160.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28.1 84.1 102.1 193 84.2 147.1 178 94.1 84.3 174 109 148 48
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185 17.2 122.1 74 33 44 62 146 174.1 53.2 122.2 22.2 94.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 163 126 143.1 95.1 22.3 196.1 72 83
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[35]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.00911871 1.05569532 0.54574840
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.947366026 0.029453765 -0.867944793
#> grade_iii, Cure model
#> 0.005277698
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 6 15.64 1 39 0 0
#> 179 18.63 1 42 0 0
#> 52 10.42 1 52 0 1
#> 81 14.06 1 34 0 0
#> 8 18.43 1 32 0 0
#> 78 23.88 1 43 0 0
#> 14 12.89 1 21 0 0
#> 180 14.82 1 37 0 0
#> 167 15.55 1 56 1 0
#> 195 11.76 1 NA 1 0
#> 181 16.46 1 45 0 1
#> 93 10.33 1 52 0 1
#> 18 15.21 1 49 1 0
#> 26 15.77 1 49 0 1
#> 168 23.72 1 70 0 0
#> 139 21.49 1 63 1 0
#> 37 12.52 1 57 1 0
#> 187 9.92 1 39 1 0
#> 36 21.19 1 48 0 1
#> 145 10.07 1 65 1 0
#> 76 19.22 1 54 0 1
#> 130 16.47 1 53 0 1
#> 86 23.81 1 58 0 1
#> 169 22.41 1 46 0 0
#> 29 15.45 1 68 1 0
#> 42 12.43 1 49 0 1
#> 14.1 12.89 1 21 0 0
#> 150 20.33 1 48 0 0
#> 66 22.13 1 53 0 0
#> 171 16.57 1 41 0 1
#> 192 16.44 1 31 1 0
#> 134 17.81 1 47 1 0
#> 166 19.98 1 48 0 0
#> 199 19.81 1 NA 0 1
#> 179.1 18.63 1 42 0 0
#> 187.1 9.92 1 39 1 0
#> 58 19.34 1 39 0 0
#> 195.1 11.76 1 NA 1 0
#> 29.1 15.45 1 68 1 0
#> 105 19.75 1 60 0 0
#> 77 7.27 1 67 0 1
#> 169.1 22.41 1 46 0 0
#> 25 6.32 1 34 1 0
#> 175 21.91 1 43 0 0
#> 37.1 12.52 1 57 1 0
#> 42.1 12.43 1 49 0 1
#> 136 21.83 1 43 0 1
#> 15 22.68 1 48 0 0
#> 105.1 19.75 1 60 0 0
#> 39 15.59 1 37 0 1
#> 194 22.40 1 38 0 1
#> 110 17.56 1 65 0 1
#> 139.1 21.49 1 63 1 0
#> 179.2 18.63 1 42 0 0
#> 26.1 15.77 1 49 0 1
#> 91 5.33 1 61 0 1
#> 49 12.19 1 48 1 0
#> 88 18.37 1 47 0 0
#> 29.2 15.45 1 68 1 0
#> 114 13.68 1 NA 0 0
#> 58.1 19.34 1 39 0 0
#> 133 14.65 1 57 0 0
#> 100 16.07 1 60 0 0
#> 145.1 10.07 1 65 1 0
#> 23 16.92 1 61 0 0
#> 37.2 12.52 1 57 1 0
#> 42.2 12.43 1 49 0 1
#> 188 16.16 1 46 0 1
#> 133.1 14.65 1 57 0 0
#> 55 19.34 1 69 0 1
#> 85 16.44 1 36 0 0
#> 194.1 22.40 1 38 0 1
#> 85.1 16.44 1 36 0 0
#> 52.1 10.42 1 52 0 1
#> 6.1 15.64 1 39 0 0
#> 190 20.81 1 42 1 0
#> 158 20.14 1 74 1 0
#> 14.2 12.89 1 21 0 0
#> 55.1 19.34 1 69 0 1
#> 49.1 12.19 1 48 1 0
#> 39.1 15.59 1 37 0 1
#> 93.1 10.33 1 52 0 1
#> 157 15.10 1 47 0 0
#> 15.1 22.68 1 48 0 0
#> 181.1 16.46 1 45 0 1
#> 37.3 12.52 1 57 1 0
#> 55.2 19.34 1 69 0 1
#> 41 18.02 1 40 1 0
#> 180.1 14.82 1 37 0 0
#> 5 16.43 1 51 0 1
#> 8.1 18.43 1 32 0 0
#> 99 21.19 1 38 0 1
#> 66.1 22.13 1 53 0 0
#> 49.2 12.19 1 48 1 0
#> 50 10.02 1 NA 1 0
#> 66.2 22.13 1 53 0 0
#> 89 11.44 1 NA 0 0
#> 5.1 16.43 1 51 0 1
#> 171.1 16.57 1 41 0 1
#> 100.1 16.07 1 60 0 0
#> 114.1 13.68 1 NA 0 0
#> 23.1 16.92 1 61 0 0
#> 85.2 16.44 1 36 0 0
#> 108 18.29 1 39 0 1
#> 184 17.77 1 38 0 0
#> 127 3.53 1 62 0 1
#> 133.2 14.65 1 57 0 0
#> 127.1 3.53 1 62 0 1
#> 166.1 19.98 1 48 0 0
#> 169.2 22.41 1 46 0 0
#> 184.1 17.77 1 38 0 0
#> 24 23.89 1 38 0 0
#> 75 24.00 0 21 1 0
#> 34 24.00 0 36 0 0
#> 98 24.00 0 34 1 0
#> 137 24.00 0 45 1 0
#> 193 24.00 0 45 0 1
#> 75.1 24.00 0 21 1 0
#> 53 24.00 0 32 0 1
#> 193.1 24.00 0 45 0 1
#> 176 24.00 0 43 0 1
#> 126 24.00 0 48 0 0
#> 178 24.00 0 52 1 0
#> 146 24.00 0 63 1 0
#> 47 24.00 0 38 0 1
#> 98.1 24.00 0 34 1 0
#> 20 24.00 0 46 1 0
#> 31 24.00 0 36 0 1
#> 94 24.00 0 51 0 1
#> 87 24.00 0 27 0 0
#> 47.1 24.00 0 38 0 1
#> 120 24.00 0 68 0 1
#> 74 24.00 0 43 0 1
#> 71 24.00 0 51 0 0
#> 163 24.00 0 66 0 0
#> 83 24.00 0 6 0 0
#> 71.1 24.00 0 51 0 0
#> 112 24.00 0 61 0 0
#> 48 24.00 0 31 1 0
#> 9 24.00 0 31 1 0
#> 146.1 24.00 0 63 1 0
#> 35 24.00 0 51 0 0
#> 176.1 24.00 0 43 0 1
#> 17 24.00 0 38 0 1
#> 44 24.00 0 56 0 0
#> 126.1 24.00 0 48 0 0
#> 65 24.00 0 57 1 0
#> 109 24.00 0 48 0 0
#> 9.1 24.00 0 31 1 0
#> 94.1 24.00 0 51 0 1
#> 148 24.00 0 61 1 0
#> 74.1 24.00 0 43 0 1
#> 146.2 24.00 0 63 1 0
#> 196 24.00 0 19 0 0
#> 64 24.00 0 43 0 0
#> 178.1 24.00 0 52 1 0
#> 54 24.00 0 53 1 0
#> 131 24.00 0 66 0 0
#> 142 24.00 0 53 0 0
#> 109.1 24.00 0 48 0 0
#> 147 24.00 0 76 1 0
#> 144 24.00 0 28 0 1
#> 143 24.00 0 51 0 0
#> 172 24.00 0 41 0 0
#> 143.1 24.00 0 51 0 0
#> 65.1 24.00 0 57 1 0
#> 83.1 24.00 0 6 0 0
#> 137.1 24.00 0 45 1 0
#> 186 24.00 0 45 1 0
#> 109.2 24.00 0 48 0 0
#> 141 24.00 0 44 1 0
#> 148.1 24.00 0 61 1 0
#> 173 24.00 0 19 0 1
#> 191 24.00 0 60 0 1
#> 67 24.00 0 25 0 0
#> 34.1 24.00 0 36 0 0
#> 144.1 24.00 0 28 0 1
#> 160 24.00 0 31 1 0
#> 162 24.00 0 51 0 0
#> 65.2 24.00 0 57 1 0
#> 65.3 24.00 0 57 1 0
#> 141.1 24.00 0 44 1 0
#> 103 24.00 0 56 1 0
#> 185 24.00 0 44 1 0
#> 53.1 24.00 0 32 0 1
#> 21 24.00 0 47 0 0
#> 17.1 24.00 0 38 0 1
#> 53.2 24.00 0 32 0 1
#> 22 24.00 0 52 1 0
#> 162.1 24.00 0 51 0 0
#> 80 24.00 0 41 0 0
#> 147.1 24.00 0 76 1 0
#> 148.2 24.00 0 61 1 0
#> 196.1 24.00 0 19 0 0
#> 12 24.00 0 63 0 0
#> 200 24.00 0 64 0 0
#> 122 24.00 0 66 0 0
#> 1 24.00 0 23 1 0
#> 152 24.00 0 36 0 1
#> 47.2 24.00 0 38 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.947 NA NA NA
#> 2 age, Cure model 0.0295 NA NA NA
#> 3 grade_ii, Cure model -0.868 NA NA NA
#> 4 grade_iii, Cure model 0.00528 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00912 NA NA NA
#> 2 grade_ii, Survival model 1.06 NA NA NA
#> 3 grade_iii, Survival model 0.546 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.947366 0.029454 -0.867945 0.005278
#>
#> Degrees of Freedom: 192 Total (i.e. Null); 189 Residual
#> Null Deviance: 266.1
#> Residual Deviance: 254.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.947366026 0.029453765 -0.867944793 0.005277698
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.00911871 1.05569532 0.54574840
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.601351597 0.300238182 0.882052527 0.748361628 0.330066180 0.006136544
#> [7] 0.758300309 0.699682936 0.641599177 0.472437669 0.900594812 0.680389213
#> [13] 0.581353449 0.019185277 0.140179778 0.787927762 0.937405854 0.159406689
#> [19] 0.919108829 0.290273628 0.462245329 0.012647254 0.043367930 0.651588914
#> [25] 0.825842733 0.758300309 0.187464600 0.088762920 0.442057035 0.492478575
#> [31] 0.381733200 0.206005128 0.300238182 0.937405854 0.243674610 0.651588914
#> [37] 0.224506784 0.955347833 0.043367930 0.964366715 0.118174533 0.787927762
#> [43] 0.825842733 0.129254593 0.026995660 0.224506784 0.621550817 0.070405921
#> [49] 0.411597985 0.140179778 0.300238182 0.581353449 0.973293115 0.854342817
#> [55] 0.350581737 0.651588914 0.243674610 0.719042229 0.561283583 0.919108829
#> [61] 0.421694538 0.787927762 0.825842733 0.551308999 0.719042229 0.243674610
#> [67] 0.492478575 0.070405921 0.492478575 0.882052527 0.601351597 0.178256435
#> [73] 0.196836000 0.758300309 0.243674610 0.854342817 0.621550817 0.900594812
#> [79] 0.690012568 0.026995660 0.472437669 0.787927762 0.243674610 0.371560645
#> [85] 0.699682936 0.531492488 0.330066180 0.159406689 0.088762920 0.854342817
#> [91] 0.088762920 0.531492488 0.442057035 0.561283583 0.421694538 0.492478575
#> [97] 0.361103079 0.391674715 0.982220371 0.719042229 0.982220371 0.206005128
#> [103] 0.043367930 0.391674715 0.001492029 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [193] 0.000000000
#>
#> $Time
#> 6 179 52 81 8 78 14 180 167 181 93 18 26
#> 15.64 18.63 10.42 14.06 18.43 23.88 12.89 14.82 15.55 16.46 10.33 15.21 15.77
#> 168 139 37 187 36 145 76 130 86 169 29 42 14.1
#> 23.72 21.49 12.52 9.92 21.19 10.07 19.22 16.47 23.81 22.41 15.45 12.43 12.89
#> 150 66 171 192 134 166 179.1 187.1 58 29.1 105 77 169.1
#> 20.33 22.13 16.57 16.44 17.81 19.98 18.63 9.92 19.34 15.45 19.75 7.27 22.41
#> 25 175 37.1 42.1 136 15 105.1 39 194 110 139.1 179.2 26.1
#> 6.32 21.91 12.52 12.43 21.83 22.68 19.75 15.59 22.40 17.56 21.49 18.63 15.77
#> 91 49 88 29.2 58.1 133 100 145.1 23 37.2 42.2 188 133.1
#> 5.33 12.19 18.37 15.45 19.34 14.65 16.07 10.07 16.92 12.52 12.43 16.16 14.65
#> 55 85 194.1 85.1 52.1 6.1 190 158 14.2 55.1 49.1 39.1 93.1
#> 19.34 16.44 22.40 16.44 10.42 15.64 20.81 20.14 12.89 19.34 12.19 15.59 10.33
#> 157 15.1 181.1 37.3 55.2 41 180.1 5 8.1 99 66.1 49.2 66.2
#> 15.10 22.68 16.46 12.52 19.34 18.02 14.82 16.43 18.43 21.19 22.13 12.19 22.13
#> 5.1 171.1 100.1 23.1 85.2 108 184 127 133.2 127.1 166.1 169.2 184.1
#> 16.43 16.57 16.07 16.92 16.44 18.29 17.77 3.53 14.65 3.53 19.98 22.41 17.77
#> 24 75 34 98 137 193 75.1 53 193.1 176 126 178 146
#> 23.89 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 47 98.1 20 31 94 87 47.1 120 74 71 163 83 71.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 112 48 9 146.1 35 176.1 17 44 126.1 65 109 9.1 94.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148 74.1 146.2 196 64 178.1 54 131 142 109.1 147 144 143
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172 143.1 65.1 83.1 137.1 186 109.2 141 148.1 173 191 67 34.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 144.1 160 162 65.2 65.3 141.1 103 185 53.1 21 17.1 53.2 22
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 162.1 80 147.1 148.2 196.1 12 200 122 1 152 47.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[36]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.01773492 0.29502692 0.19600476
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.178781433 -0.003308271 -0.020141721
#> grade_iii, Cure model
#> 0.550863778
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 90 20.94 1 50 0 1
#> 37 12.52 1 57 1 0
#> 15 22.68 1 48 0 0
#> 175 21.91 1 43 0 0
#> 40 18.00 1 28 1 0
#> 69 23.23 1 25 0 1
#> 184 17.77 1 38 0 0
#> 179 18.63 1 42 0 0
#> 96 14.54 1 33 0 1
#> 99 21.19 1 38 0 1
#> 101 9.97 1 10 0 1
#> 92 22.92 1 47 0 1
#> 92.1 22.92 1 47 0 1
#> 18 15.21 1 49 1 0
#> 69.1 23.23 1 25 0 1
#> 4 17.64 1 NA 0 1
#> 139 21.49 1 63 1 0
#> 96.1 14.54 1 33 0 1
#> 170 19.54 1 43 0 1
#> 139.1 21.49 1 63 1 0
#> 5 16.43 1 51 0 1
#> 100 16.07 1 60 0 0
#> 180 14.82 1 37 0 0
#> 43 12.10 1 61 0 1
#> 91 5.33 1 61 0 1
#> 69.2 23.23 1 25 0 1
#> 51 18.23 1 83 0 1
#> 37.1 12.52 1 57 1 0
#> 159 10.55 1 50 0 1
#> 130 16.47 1 53 0 1
#> 78 23.88 1 43 0 0
#> 190 20.81 1 42 1 0
#> 81 14.06 1 34 0 0
#> 140 12.68 1 59 1 0
#> 6 15.64 1 39 0 0
#> 4.1 17.64 1 NA 0 1
#> 134 17.81 1 47 1 0
#> 110 17.56 1 65 0 1
#> 56 12.21 1 60 0 0
#> 140.1 12.68 1 59 1 0
#> 100.1 16.07 1 60 0 0
#> 100.2 16.07 1 60 0 0
#> 58 19.34 1 39 0 0
#> 155 13.08 1 26 0 0
#> 24 23.89 1 38 0 0
#> 23 16.92 1 61 0 0
#> 10 10.53 1 34 0 0
#> 159.1 10.55 1 50 0 1
#> 136 21.83 1 43 0 1
#> 30 17.43 1 78 0 0
#> 77 7.27 1 67 0 1
#> 76 19.22 1 54 0 1
#> 199 19.81 1 NA 0 1
#> 70 7.38 1 30 1 0
#> 41 18.02 1 40 1 0
#> 100.3 16.07 1 60 0 0
#> 128 20.35 1 35 0 1
#> 183 9.24 1 67 1 0
#> 140.2 12.68 1 59 1 0
#> 155.1 13.08 1 26 0 0
#> 133 14.65 1 57 0 0
#> 190.1 20.81 1 42 1 0
#> 136.1 21.83 1 43 0 1
#> 90.1 20.94 1 50 0 1
#> 180.1 14.82 1 37 0 0
#> 4.2 17.64 1 NA 0 1
#> 66 22.13 1 53 0 0
#> 59 10.16 1 NA 1 0
#> 188 16.16 1 46 0 1
#> 55 19.34 1 69 0 1
#> 134.1 17.81 1 47 1 0
#> 36 21.19 1 48 0 1
#> 81.1 14.06 1 34 0 0
#> 58.1 19.34 1 39 0 0
#> 6.1 15.64 1 39 0 0
#> 139.2 21.49 1 63 1 0
#> 32 20.90 1 37 1 0
#> 130.1 16.47 1 53 0 1
#> 190.2 20.81 1 42 1 0
#> 150 20.33 1 48 0 0
#> 63 22.77 1 31 1 0
#> 175.1 21.91 1 43 0 0
#> 24.1 23.89 1 38 0 0
#> 125 15.65 1 67 1 0
#> 166 19.98 1 48 0 0
#> 77.1 7.27 1 67 0 1
#> 41.1 18.02 1 40 1 0
#> 190.3 20.81 1 42 1 0
#> 124 9.73 1 NA 1 0
#> 8 18.43 1 32 0 0
#> 93 10.33 1 52 0 1
#> 37.2 12.52 1 57 1 0
#> 166.1 19.98 1 48 0 0
#> 79 16.23 1 54 1 0
#> 155.2 13.08 1 26 0 0
#> 78.1 23.88 1 43 0 0
#> 90.2 20.94 1 50 0 1
#> 127 3.53 1 62 0 1
#> 37.3 12.52 1 57 1 0
#> 91.1 5.33 1 61 0 1
#> 14 12.89 1 21 0 0
#> 127.1 3.53 1 62 0 1
#> 101.1 9.97 1 10 0 1
#> 134.2 17.81 1 47 1 0
#> 26 15.77 1 49 0 1
#> 76.1 19.22 1 54 0 1
#> 184.1 17.77 1 38 0 0
#> 40.1 18.00 1 28 1 0
#> 96.2 14.54 1 33 0 1
#> 153 21.33 1 55 1 0
#> 79.1 16.23 1 54 1 0
#> 25 6.32 1 34 1 0
#> 62 24.00 0 71 0 0
#> 165 24.00 0 47 0 0
#> 126 24.00 0 48 0 0
#> 65 24.00 0 57 1 0
#> 151 24.00 0 42 0 0
#> 161 24.00 0 45 0 0
#> 142 24.00 0 53 0 0
#> 3 24.00 0 31 1 0
#> 47 24.00 0 38 0 1
#> 21 24.00 0 47 0 0
#> 94 24.00 0 51 0 1
#> 138 24.00 0 44 1 0
#> 112 24.00 0 61 0 0
#> 46 24.00 0 71 0 0
#> 148 24.00 0 61 1 0
#> 138.1 24.00 0 44 1 0
#> 46.1 24.00 0 71 0 0
#> 103 24.00 0 56 1 0
#> 72 24.00 0 40 0 1
#> 20 24.00 0 46 1 0
#> 173 24.00 0 19 0 1
#> 126.1 24.00 0 48 0 0
#> 22 24.00 0 52 1 0
#> 173.1 24.00 0 19 0 1
#> 22.1 24.00 0 52 1 0
#> 143 24.00 0 51 0 0
#> 137 24.00 0 45 1 0
#> 182 24.00 0 35 0 0
#> 80 24.00 0 41 0 0
#> 22.2 24.00 0 52 1 0
#> 54 24.00 0 53 1 0
#> 83 24.00 0 6 0 0
#> 75 24.00 0 21 1 0
#> 74 24.00 0 43 0 1
#> 165.1 24.00 0 47 0 0
#> 172 24.00 0 41 0 0
#> 135 24.00 0 58 1 0
#> 21.1 24.00 0 47 0 0
#> 165.2 24.00 0 47 0 0
#> 191 24.00 0 60 0 1
#> 148.1 24.00 0 61 1 0
#> 103.1 24.00 0 56 1 0
#> 82 24.00 0 34 0 0
#> 87 24.00 0 27 0 0
#> 7 24.00 0 37 1 0
#> 71 24.00 0 51 0 0
#> 19 24.00 0 57 0 1
#> 103.2 24.00 0 56 1 0
#> 38 24.00 0 31 1 0
#> 1 24.00 0 23 1 0
#> 121 24.00 0 57 1 0
#> 71.1 24.00 0 51 0 0
#> 80.1 24.00 0 41 0 0
#> 48 24.00 0 31 1 0
#> 119 24.00 0 17 0 0
#> 46.2 24.00 0 71 0 0
#> 27 24.00 0 63 1 0
#> 104 24.00 0 50 1 0
#> 198 24.00 0 66 0 1
#> 182.1 24.00 0 35 0 0
#> 46.3 24.00 0 71 0 0
#> 75.1 24.00 0 21 1 0
#> 176 24.00 0 43 0 1
#> 116 24.00 0 58 0 1
#> 112.1 24.00 0 61 0 0
#> 33 24.00 0 53 0 0
#> 176.1 24.00 0 43 0 1
#> 44 24.00 0 56 0 0
#> 116.1 24.00 0 58 0 1
#> 22.3 24.00 0 52 1 0
#> 146 24.00 0 63 1 0
#> 120 24.00 0 68 0 1
#> 137.1 24.00 0 45 1 0
#> 27.1 24.00 0 63 1 0
#> 87.1 24.00 0 27 0 0
#> 44.1 24.00 0 56 0 0
#> 19.1 24.00 0 57 0 1
#> 185 24.00 0 44 1 0
#> 53 24.00 0 32 0 1
#> 71.2 24.00 0 51 0 0
#> 94.1 24.00 0 51 0 1
#> 198.1 24.00 0 66 0 1
#> 94.2 24.00 0 51 0 1
#> 84 24.00 0 39 0 1
#> 172.1 24.00 0 41 0 0
#> 9 24.00 0 31 1 0
#> 47.1 24.00 0 38 0 1
#> 152 24.00 0 36 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.179 NA NA NA
#> 2 age, Cure model -0.00331 NA NA NA
#> 3 grade_ii, Cure model -0.0201 NA NA NA
#> 4 grade_iii, Cure model 0.551 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0177 NA NA NA
#> 2 grade_ii, Survival model 0.295 NA NA NA
#> 3 grade_iii, Survival model 0.196 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.178781 -0.003308 -0.020142 0.550864
#>
#> Degrees of Freedom: 193 Total (i.e. Null); 190 Residual
#> Null Deviance: 267.3
#> Residual Deviance: 264 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.178781433 -0.003308271 -0.020141721 0.550863778
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.01773492 0.29502692 0.19600476
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.5667030 0.9236825 0.4138458 0.4477733 0.7343423 0.2875012 0.7629282
#> [8] 0.7031308 0.8738409 0.5472794 0.9613403 0.3567709 0.3567709 0.8563774
#> [15] 0.2875012 0.5047049 0.8738409 0.6624418 0.5047049 0.8002694 0.8199548
#> [22] 0.8607895 0.9427720 0.9863926 0.2875012 0.7160963 0.9236825 0.9465455
#> [29] 0.7900582 0.2253529 0.6016557 0.8865511 0.9116653 0.8474750 0.7461364
#> [36] 0.7740073 0.9389590 0.9116653 0.8199548 0.8199548 0.6696808 0.8949781
#> [43] 0.1353636 0.7847916 0.9539623 0.9465455 0.4775995 0.7794552 0.9758629
#> [50] 0.6900470 0.9722650 0.7223151 0.8199548 0.6324601 0.9686499 0.9116653
#> [57] 0.8949781 0.8695085 0.6016557 0.4775995 0.5667030 0.8607895 0.4313293
#> [64] 0.8151029 0.6696808 0.7461364 0.5472794 0.8865511 0.6696808 0.8474750
#> [71] 0.5047049 0.5929732 0.7900582 0.6016557 0.6401850 0.3953113 0.4477733
#> [78] 0.1353636 0.8429647 0.6477866 0.9758629 0.7223151 0.6016557 0.7096362
#> [85] 0.9576659 0.9236825 0.6477866 0.8053265 0.8949781 0.2253529 0.5667030
#> [92] 0.9932581 0.9236825 0.9863926 0.9074856 0.9932581 0.9613403 0.7461364
#> [99] 0.8383707 0.6900470 0.7629282 0.7343423 0.8738409 0.5368772 0.8053265
#> [106] 0.9828907 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [183] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [190] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#>
#> $Time
#> 90 37 15 175 40 69 184 179 96 99 101 92 92.1
#> 20.94 12.52 22.68 21.91 18.00 23.23 17.77 18.63 14.54 21.19 9.97 22.92 22.92
#> 18 69.1 139 96.1 170 139.1 5 100 180 43 91 69.2 51
#> 15.21 23.23 21.49 14.54 19.54 21.49 16.43 16.07 14.82 12.10 5.33 23.23 18.23
#> 37.1 159 130 78 190 81 140 6 134 110 56 140.1 100.1
#> 12.52 10.55 16.47 23.88 20.81 14.06 12.68 15.64 17.81 17.56 12.21 12.68 16.07
#> 100.2 58 155 24 23 10 159.1 136 30 77 76 70 41
#> 16.07 19.34 13.08 23.89 16.92 10.53 10.55 21.83 17.43 7.27 19.22 7.38 18.02
#> 100.3 128 183 140.2 155.1 133 190.1 136.1 90.1 180.1 66 188 55
#> 16.07 20.35 9.24 12.68 13.08 14.65 20.81 21.83 20.94 14.82 22.13 16.16 19.34
#> 134.1 36 81.1 58.1 6.1 139.2 32 130.1 190.2 150 63 175.1 24.1
#> 17.81 21.19 14.06 19.34 15.64 21.49 20.90 16.47 20.81 20.33 22.77 21.91 23.89
#> 125 166 77.1 41.1 190.3 8 93 37.2 166.1 79 155.2 78.1 90.2
#> 15.65 19.98 7.27 18.02 20.81 18.43 10.33 12.52 19.98 16.23 13.08 23.88 20.94
#> 127 37.3 91.1 14 127.1 101.1 134.2 26 76.1 184.1 40.1 96.2 153
#> 3.53 12.52 5.33 12.89 3.53 9.97 17.81 15.77 19.22 17.77 18.00 14.54 21.33
#> 79.1 25 62 165 126 65 151 161 142 3 47 21 94
#> 16.23 6.32 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 138 112 46 148 138.1 46.1 103 72 20 173 126.1 22 173.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 22.1 143 137 182 80 22.2 54 83 75 74 165.1 172 135
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 21.1 165.2 191 148.1 103.1 82 87 7 71 19 103.2 38 1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 121 71.1 80.1 48 119 46.2 27 104 198 182.1 46.3 75.1 176
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116 112.1 33 176.1 44 116.1 22.3 146 120 137.1 27.1 87.1 44.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 19.1 185 53 71.2 94.1 198.1 94.2 84 172.1 9 47.1 152
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[37]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01141556 0.98295095 0.39565500
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.210677637 0.002515566 -0.272056552
#> grade_iii, Cure model
#> 1.151558101
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 96 14.54 1 33 0 1
#> 188 16.16 1 46 0 1
#> 59 10.16 1 NA 1 0
#> 61 10.12 1 36 0 1
#> 76 19.22 1 54 0 1
#> 61.1 10.12 1 36 0 1
#> 101 9.97 1 10 0 1
#> 153 21.33 1 55 1 0
#> 61.2 10.12 1 36 0 1
#> 111 17.45 1 47 0 1
#> 96.1 14.54 1 33 0 1
#> 169 22.41 1 46 0 0
#> 86 23.81 1 58 0 1
#> 66 22.13 1 53 0 0
#> 105 19.75 1 60 0 0
#> 136 21.83 1 43 0 1
#> 52 10.42 1 52 0 1
#> 134 17.81 1 47 1 0
#> 192 16.44 1 31 1 0
#> 15 22.68 1 48 0 0
#> 111.1 17.45 1 47 0 1
#> 39 15.59 1 37 0 1
#> 91 5.33 1 61 0 1
#> 188.1 16.16 1 46 0 1
#> 134.1 17.81 1 47 1 0
#> 133 14.65 1 57 0 0
#> 125 15.65 1 67 1 0
#> 92 22.92 1 47 0 1
#> 117 17.46 1 26 0 1
#> 61.3 10.12 1 36 0 1
#> 111.2 17.45 1 47 0 1
#> 166 19.98 1 48 0 0
#> 127 3.53 1 62 0 1
#> 175 21.91 1 43 0 0
#> 5 16.43 1 51 0 1
#> 170 19.54 1 43 0 1
#> 69 23.23 1 25 0 1
#> 61.4 10.12 1 36 0 1
#> 23 16.92 1 61 0 0
#> 157 15.10 1 47 0 0
#> 124 9.73 1 NA 1 0
#> 92.1 22.92 1 47 0 1
#> 133.1 14.65 1 57 0 0
#> 8 18.43 1 32 0 0
#> 150 20.33 1 48 0 0
#> 187 9.92 1 39 1 0
#> 184 17.77 1 38 0 0
#> 184.1 17.77 1 38 0 0
#> 51 18.23 1 83 0 1
#> 66.1 22.13 1 53 0 0
#> 170.1 19.54 1 43 0 1
#> 29 15.45 1 68 1 0
#> 77 7.27 1 67 0 1
#> 66.2 22.13 1 53 0 0
#> 14 12.89 1 21 0 0
#> 92.2 22.92 1 47 0 1
#> 167 15.55 1 56 1 0
#> 164 23.60 1 76 0 1
#> 89 11.44 1 NA 0 0
#> 66.3 22.13 1 53 0 0
#> 189 10.51 1 NA 1 0
#> 88 18.37 1 47 0 0
#> 93 10.33 1 52 0 1
#> 97 19.14 1 65 0 1
#> 199 19.81 1 NA 0 1
#> 149 8.37 1 33 1 0
#> 164.1 23.60 1 76 0 1
#> 108 18.29 1 39 0 1
#> 37 12.52 1 57 1 0
#> 153.1 21.33 1 55 1 0
#> 195 11.76 1 NA 1 0
#> 86.1 23.81 1 58 0 1
#> 41 18.02 1 40 1 0
#> 30 17.43 1 78 0 0
#> 99 21.19 1 38 0 1
#> 39.1 15.59 1 37 0 1
#> 154 12.63 1 20 1 0
#> 49 12.19 1 48 1 0
#> 78 23.88 1 43 0 0
#> 37.1 12.52 1 57 1 0
#> 91.1 5.33 1 61 0 1
#> 180 14.82 1 37 0 0
#> 140 12.68 1 59 1 0
#> 181 16.46 1 45 0 1
#> 10 10.53 1 34 0 0
#> 125.1 15.65 1 67 1 0
#> 15.1 22.68 1 48 0 0
#> 18 15.21 1 49 1 0
#> 90 20.94 1 50 0 1
#> 117.1 17.46 1 26 0 1
#> 166.1 19.98 1 48 0 0
#> 100 16.07 1 60 0 0
#> 139 21.49 1 63 1 0
#> 32 20.90 1 37 1 0
#> 157.1 15.10 1 47 0 0
#> 24 23.89 1 38 0 0
#> 136.1 21.83 1 43 0 1
#> 43 12.10 1 61 0 1
#> 155 13.08 1 26 0 0
#> 140.1 12.68 1 59 1 0
#> 24.1 23.89 1 38 0 0
#> 149.1 8.37 1 33 1 0
#> 189.1 10.51 1 NA 1 0
#> 90.1 20.94 1 50 0 1
#> 43.1 12.10 1 61 0 1
#> 99.1 21.19 1 38 0 1
#> 189.2 10.51 1 NA 1 0
#> 159 10.55 1 50 0 1
#> 99.2 21.19 1 38 0 1
#> 114 13.68 1 NA 0 0
#> 125.2 15.65 1 67 1 0
#> 85 16.44 1 36 0 0
#> 72 24.00 0 40 0 1
#> 151 24.00 0 42 0 0
#> 7 24.00 0 37 1 0
#> 162 24.00 0 51 0 0
#> 132 24.00 0 55 0 0
#> 126 24.00 0 48 0 0
#> 84 24.00 0 39 0 1
#> 95 24.00 0 68 0 1
#> 151.1 24.00 0 42 0 0
#> 22 24.00 0 52 1 0
#> 185 24.00 0 44 1 0
#> 142 24.00 0 53 0 0
#> 48 24.00 0 31 1 0
#> 3 24.00 0 31 1 0
#> 193 24.00 0 45 0 1
#> 73 24.00 0 NA 0 1
#> 162.1 24.00 0 51 0 0
#> 65 24.00 0 57 1 0
#> 73.1 24.00 0 NA 0 1
#> 2 24.00 0 9 0 0
#> 67 24.00 0 25 0 0
#> 172 24.00 0 41 0 0
#> 27 24.00 0 63 1 0
#> 112 24.00 0 61 0 0
#> 44 24.00 0 56 0 0
#> 138 24.00 0 44 1 0
#> 156 24.00 0 50 1 0
#> 115 24.00 0 NA 1 0
#> 144 24.00 0 28 0 1
#> 17 24.00 0 38 0 1
#> 20 24.00 0 46 1 0
#> 118 24.00 0 44 1 0
#> 196 24.00 0 19 0 0
#> 104 24.00 0 50 1 0
#> 185.1 24.00 0 44 1 0
#> 21 24.00 0 47 0 0
#> 22.1 24.00 0 52 1 0
#> 119 24.00 0 17 0 0
#> 120 24.00 0 68 0 1
#> 176 24.00 0 43 0 1
#> 44.1 24.00 0 56 0 0
#> 146 24.00 0 63 1 0
#> 178 24.00 0 52 1 0
#> 196.1 24.00 0 19 0 0
#> 95.1 24.00 0 68 0 1
#> 174 24.00 0 49 1 0
#> 174.1 24.00 0 49 1 0
#> 47 24.00 0 38 0 1
#> 119.1 24.00 0 17 0 0
#> 121 24.00 0 57 1 0
#> 20.1 24.00 0 46 1 0
#> 135 24.00 0 58 1 0
#> 122 24.00 0 66 0 0
#> 141 24.00 0 44 1 0
#> 46 24.00 0 71 0 0
#> 17.1 24.00 0 38 0 1
#> 148 24.00 0 61 1 0
#> 163 24.00 0 66 0 0
#> 75 24.00 0 21 1 0
#> 120.1 24.00 0 68 0 1
#> 53 24.00 0 32 0 1
#> 115.1 24.00 0 NA 1 0
#> 95.2 24.00 0 68 0 1
#> 172.1 24.00 0 41 0 0
#> 116 24.00 0 58 0 1
#> 118.1 24.00 0 44 1 0
#> 67.1 24.00 0 25 0 0
#> 35 24.00 0 51 0 0
#> 62 24.00 0 71 0 0
#> 104.1 24.00 0 50 1 0
#> 3.1 24.00 0 31 1 0
#> 38 24.00 0 31 1 0
#> 104.2 24.00 0 50 1 0
#> 185.2 24.00 0 44 1 0
#> 200 24.00 0 64 0 0
#> 178.1 24.00 0 52 1 0
#> 173 24.00 0 19 0 1
#> 72.1 24.00 0 40 0 1
#> 131 24.00 0 66 0 0
#> 163.1 24.00 0 66 0 0
#> 126.1 24.00 0 48 0 0
#> 46.1 24.00 0 71 0 0
#> 161 24.00 0 45 0 0
#> 21.1 24.00 0 47 0 0
#> 146.1 24.00 0 63 1 0
#> 151.2 24.00 0 42 0 0
#> 138.1 24.00 0 44 1 0
#> 46.2 24.00 0 71 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.211 NA NA NA
#> 2 age, Cure model 0.00252 NA NA NA
#> 3 grade_ii, Cure model -0.272 NA NA NA
#> 4 grade_iii, Cure model 1.15 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0114 NA NA NA
#> 2 grade_ii, Survival model 0.983 NA NA NA
#> 3 grade_iii, Survival model 0.396 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.210678 0.002516 -0.272057 1.151558
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 257.3
#> Residual Deviance: 241.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.210677637 0.002515566 -0.272056552 1.151558101
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01141556 0.98295095 0.39565500
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.698786995 0.530926293 0.866717407 0.302916301 0.866717407 0.917985596
#> [7] 0.168685417 0.866717407 0.437214255 0.698786995 0.083991619 0.014654107
#> [13] 0.092680733 0.272821448 0.138440651 0.845749692 0.376291402 0.499492391
#> [19] 0.068146287 0.437214255 0.593821176 0.969271925 0.530926293 0.376291402
#> [25] 0.677512418 0.562686334 0.047701034 0.416853946 0.866717407 0.437214255
#> [31] 0.253328738 0.989702698 0.128155979 0.520352908 0.282930831 0.040152092
#> [37] 0.866717407 0.478192858 0.646105900 0.047701034 0.677512418 0.323477648
#> [43] 0.243706256 0.928437452 0.396390007 0.396390007 0.355063772 0.092680733
#> [49] 0.282930831 0.625280851 0.959058346 0.092680733 0.730801107 0.047701034
#> [55] 0.614783048 0.026207653 0.092680733 0.333909698 0.856222022 0.313147563
#> [61] 0.938806185 0.026207653 0.344478873 0.773284786 0.168685417 0.014654107
#> [67] 0.365784227 0.467673388 0.187485826 0.593821176 0.762779430 0.793933213
#> [73] 0.008676893 0.773284786 0.969271925 0.666950215 0.741586796 0.488829704
#> [79] 0.835300600 0.562686334 0.068146287 0.635738347 0.215125865 0.416853946
#> [85] 0.253328738 0.551963322 0.158511270 0.234241454 0.646105900 0.001854410
#> [91] 0.138440651 0.804251837 0.720049245 0.741586796 0.001854410 0.938806185
#> [97] 0.215125865 0.804251837 0.187485826 0.824893387 0.187485826 0.562686334
#> [103] 0.499492391 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000
#>
#> $Time
#> 96 188 61 76 61.1 101 153 61.2 111 96.1 169 86 66
#> 14.54 16.16 10.12 19.22 10.12 9.97 21.33 10.12 17.45 14.54 22.41 23.81 22.13
#> 105 136 52 134 192 15 111.1 39 91 188.1 134.1 133 125
#> 19.75 21.83 10.42 17.81 16.44 22.68 17.45 15.59 5.33 16.16 17.81 14.65 15.65
#> 92 117 61.3 111.2 166 127 175 5 170 69 61.4 23 157
#> 22.92 17.46 10.12 17.45 19.98 3.53 21.91 16.43 19.54 23.23 10.12 16.92 15.10
#> 92.1 133.1 8 150 187 184 184.1 51 66.1 170.1 29 77 66.2
#> 22.92 14.65 18.43 20.33 9.92 17.77 17.77 18.23 22.13 19.54 15.45 7.27 22.13
#> 14 92.2 167 164 66.3 88 93 97 149 164.1 108 37 153.1
#> 12.89 22.92 15.55 23.60 22.13 18.37 10.33 19.14 8.37 23.60 18.29 12.52 21.33
#> 86.1 41 30 99 39.1 154 49 78 37.1 91.1 180 140 181
#> 23.81 18.02 17.43 21.19 15.59 12.63 12.19 23.88 12.52 5.33 14.82 12.68 16.46
#> 10 125.1 15.1 18 90 117.1 166.1 100 139 32 157.1 24 136.1
#> 10.53 15.65 22.68 15.21 20.94 17.46 19.98 16.07 21.49 20.90 15.10 23.89 21.83
#> 43 155 140.1 24.1 149.1 90.1 43.1 99.1 159 99.2 125.2 85 72
#> 12.10 13.08 12.68 23.89 8.37 20.94 12.10 21.19 10.55 21.19 15.65 16.44 24.00
#> 151 7 162 132 126 84 95 151.1 22 185 142 48 3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193 162.1 65 2 67 172 27 112 44 138 156 144 17
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20 118 196 104 185.1 21 22.1 119 120 176 44.1 146 178
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 196.1 95.1 174 174.1 47 119.1 121 20.1 135 122 141 46 17.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148 163 75 120.1 53 95.2 172.1 116 118.1 67.1 35 62 104.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3.1 38 104.2 185.2 200 178.1 173 72.1 131 163.1 126.1 46.1 161
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 21.1 146.1 151.2 138.1 46.2
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[38]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.004194738 0.911042363 0.494282999
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.12637138 0.02438264 -0.29031349
#> grade_iii, Cure model
#> 0.72882937
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 183 9.24 1 67 1 0
#> 189 10.51 1 NA 1 0
#> 197 21.60 1 69 1 0
#> 123 13.00 1 44 1 0
#> 164 23.60 1 76 0 1
#> 63 22.77 1 31 1 0
#> 110 17.56 1 65 0 1
#> 59 10.16 1 NA 1 0
#> 128 20.35 1 35 0 1
#> 125 15.65 1 67 1 0
#> 92 22.92 1 47 0 1
#> 42 12.43 1 49 0 1
#> 179 18.63 1 42 0 0
#> 154 12.63 1 20 1 0
#> 177 12.53 1 75 0 0
#> 59.1 10.16 1 NA 1 0
#> 4 17.64 1 NA 0 1
#> 37 12.52 1 57 1 0
#> 56 12.21 1 60 0 0
#> 37.1 12.52 1 57 1 0
#> 78 23.88 1 43 0 0
#> 91 5.33 1 61 0 1
#> 192 16.44 1 31 1 0
#> 66 22.13 1 53 0 0
#> 43 12.10 1 61 0 1
#> 76 19.22 1 54 0 1
#> 106 16.67 1 49 1 0
#> 175 21.91 1 43 0 0
#> 136 21.83 1 43 0 1
#> 195 11.76 1 NA 1 0
#> 189.1 10.51 1 NA 1 0
#> 4.1 17.64 1 NA 0 1
#> 111 17.45 1 47 0 1
#> 188 16.16 1 46 0 1
#> 51 18.23 1 83 0 1
#> 56.1 12.21 1 60 0 0
#> 111.1 17.45 1 47 0 1
#> 93 10.33 1 52 0 1
#> 24 23.89 1 38 0 0
#> 168 23.72 1 70 0 0
#> 99 21.19 1 38 0 1
#> 92.1 22.92 1 47 0 1
#> 114 13.68 1 NA 0 0
#> 92.2 22.92 1 47 0 1
#> 55 19.34 1 69 0 1
#> 29 15.45 1 68 1 0
#> 149 8.37 1 33 1 0
#> 123.1 13.00 1 44 1 0
#> 192.1 16.44 1 31 1 0
#> 140 12.68 1 59 1 0
#> 117 17.46 1 26 0 1
#> 96 14.54 1 33 0 1
#> 189.2 10.51 1 NA 1 0
#> 59.2 10.16 1 NA 1 0
#> 168.1 23.72 1 70 0 0
#> 69 23.23 1 25 0 1
#> 105 19.75 1 60 0 0
#> 39 15.59 1 37 0 1
#> 79 16.23 1 54 1 0
#> 110.1 17.56 1 65 0 1
#> 85 16.44 1 36 0 0
#> 56.2 12.21 1 60 0 0
#> 23 16.92 1 61 0 0
#> 57 14.46 1 45 0 1
#> 51.1 18.23 1 83 0 1
#> 8 18.43 1 32 0 0
#> 113 22.86 1 34 0 0
#> 188.1 16.16 1 46 0 1
#> 101 9.97 1 10 0 1
#> 6 15.64 1 39 0 0
#> 41 18.02 1 40 1 0
#> 5 16.43 1 51 0 1
#> 175.1 21.91 1 43 0 0
#> 129 23.41 1 53 1 0
#> 30 17.43 1 78 0 0
#> 195.1 11.76 1 NA 1 0
#> 199 19.81 1 NA 0 1
#> 40 18.00 1 28 1 0
#> 18 15.21 1 49 1 0
#> 85.1 16.44 1 36 0 0
#> 13 14.34 1 54 0 1
#> 58 19.34 1 39 0 0
#> 175.2 21.91 1 43 0 0
#> 8.1 18.43 1 32 0 0
#> 179.1 18.63 1 42 0 0
#> 187 9.92 1 39 1 0
#> 45 17.42 1 54 0 1
#> 81 14.06 1 34 0 0
#> 145 10.07 1 65 1 0
#> 180 14.82 1 37 0 0
#> 164.1 23.60 1 76 0 1
#> 26 15.77 1 49 0 1
#> 79.1 16.23 1 54 1 0
#> 86 23.81 1 58 0 1
#> 166 19.98 1 48 0 0
#> 197.1 21.60 1 69 1 0
#> 45.1 17.42 1 54 0 1
#> 166.1 19.98 1 48 0 0
#> 183.1 9.24 1 67 1 0
#> 189.3 10.51 1 NA 1 0
#> 32 20.90 1 37 1 0
#> 93.1 10.33 1 52 0 1
#> 16 8.71 1 71 0 1
#> 168.2 23.72 1 70 0 0
#> 70 7.38 1 30 1 0
#> 8.2 18.43 1 32 0 0
#> 24.1 23.89 1 38 0 0
#> 169 22.41 1 46 0 0
#> 97 19.14 1 65 0 1
#> 127 3.53 1 62 0 1
#> 155 13.08 1 26 0 0
#> 139 21.49 1 63 1 0
#> 64 24.00 0 43 0 0
#> 3 24.00 0 31 1 0
#> 156 24.00 0 50 1 0
#> 46 24.00 0 71 0 0
#> 75 24.00 0 21 1 0
#> 64.1 24.00 0 43 0 0
#> 72 24.00 0 40 0 1
#> 102 24.00 0 49 0 0
#> 104 24.00 0 50 1 0
#> 120 24.00 0 68 0 1
#> 33 24.00 0 53 0 0
#> 118 24.00 0 44 1 0
#> 27 24.00 0 63 1 0
#> 20 24.00 0 46 1 0
#> 198 24.00 0 66 0 1
#> 71 24.00 0 51 0 0
#> 35 24.00 0 51 0 0
#> 116 24.00 0 58 0 1
#> 72.1 24.00 0 40 0 1
#> 182 24.00 0 35 0 0
#> 186 24.00 0 45 1 0
#> 83 24.00 0 6 0 0
#> 35.1 24.00 0 51 0 0
#> 109 24.00 0 48 0 0
#> 141 24.00 0 44 1 0
#> 1 24.00 0 23 1 0
#> 54 24.00 0 53 1 0
#> 104.1 24.00 0 50 1 0
#> 176 24.00 0 43 0 1
#> 62 24.00 0 71 0 0
#> 191 24.00 0 60 0 1
#> 48 24.00 0 31 1 0
#> 83.1 24.00 0 6 0 0
#> 98 24.00 0 34 1 0
#> 118.1 24.00 0 44 1 0
#> 48.1 24.00 0 31 1 0
#> 9 24.00 0 31 1 0
#> 126 24.00 0 48 0 0
#> 9.1 24.00 0 31 1 0
#> 64.2 24.00 0 43 0 0
#> 65 24.00 0 57 1 0
#> 65.1 24.00 0 57 1 0
#> 53 24.00 0 32 0 1
#> 132 24.00 0 55 0 0
#> 7 24.00 0 37 1 0
#> 9.2 24.00 0 31 1 0
#> 7.1 24.00 0 37 1 0
#> 87 24.00 0 27 0 0
#> 138 24.00 0 44 1 0
#> 3.1 24.00 0 31 1 0
#> 72.2 24.00 0 40 0 1
#> 20.1 24.00 0 46 1 0
#> 17 24.00 0 38 0 1
#> 191.1 24.00 0 60 0 1
#> 161 24.00 0 45 0 0
#> 80 24.00 0 41 0 0
#> 28 24.00 0 67 1 0
#> 20.2 24.00 0 46 1 0
#> 160 24.00 0 31 1 0
#> 28.1 24.00 0 67 1 0
#> 44 24.00 0 56 0 0
#> 74 24.00 0 43 0 1
#> 31 24.00 0 36 0 1
#> 144 24.00 0 28 0 1
#> 131 24.00 0 66 0 0
#> 54.1 24.00 0 53 1 0
#> 82 24.00 0 34 0 0
#> 83.2 24.00 0 6 0 0
#> 141.1 24.00 0 44 1 0
#> 132.1 24.00 0 55 0 0
#> 1.1 24.00 0 23 1 0
#> 185 24.00 0 44 1 0
#> 151 24.00 0 42 0 0
#> 67 24.00 0 25 0 0
#> 118.2 24.00 0 44 1 0
#> 193 24.00 0 45 0 1
#> 112 24.00 0 61 0 0
#> 162 24.00 0 51 0 0
#> 151.1 24.00 0 42 0 0
#> 74.1 24.00 0 43 0 1
#> 103 24.00 0 56 1 0
#> 38 24.00 0 31 1 0
#> 33.1 24.00 0 53 0 0
#> 200 24.00 0 64 0 0
#> 11 24.00 0 42 0 1
#> 131.1 24.00 0 66 0 0
#> 196 24.00 0 19 0 0
#> 185.1 24.00 0 44 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.13 NA NA NA
#> 2 age, Cure model 0.0244 NA NA NA
#> 3 grade_ii, Cure model -0.290 NA NA NA
#> 4 grade_iii, Cure model 0.729 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00419 NA NA NA
#> 2 grade_ii, Survival model 0.911 NA NA NA
#> 3 grade_iii, Survival model 0.494 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.12637 0.02438 -0.29031 0.72883
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 258.6
#> Residual Deviance: 244.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.12637138 0.02438264 -0.29031349 0.72882937
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.004194738 0.911042363 0.494282999
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.94735105 0.30333570 0.81230144 0.11314833 0.21981574 0.53302828
#> [7] 0.35791940 0.71855371 0.17161535 0.86877964 0.44085934 0.83684847
#> [13] 0.84490611 0.85298454 0.87668924 0.85298454 0.03582953 0.98511727
#> [19] 0.62938724 0.24367952 0.90034582 0.42011080 0.61990040 0.25578416
#> [25] 0.29120425 0.56234735 0.69222369 0.49226456 0.87668924 0.56234735
#> [31] 0.90828256 0.01108913 0.06898100 0.33659679 0.17161535 0.17161535
#> [37] 0.39940248 0.74463031 0.97012083 0.81230144 0.62938724 0.82868974
#> [43] 0.55257034 0.77019450 0.06898100 0.15779784 0.38888954 0.73596048
#> [49] 0.67452486 0.53302828 0.62938724 0.87668924 0.61026241 0.77865207
#> [55] 0.49226456 0.46145765 0.20712661 0.69222369 0.93183221 0.72724923
#> [61] 0.51288623 0.66537922 0.25578416 0.14338051 0.58150303 0.52307467
#> [67] 0.75321322 0.62938724 0.78707693 0.39940248 0.25578416 0.46145765
#> [73] 0.44085934 0.93962725 0.59120604 0.79547420 0.92399970 0.76169706
#> [79] 0.11314833 0.70976484 0.67452486 0.05311353 0.36827020 0.30333570
#> [85] 0.59120604 0.36827020 0.94735105 0.34744275 0.90828256 0.96251953
#> [91] 0.06898100 0.97765335 0.46145765 0.01108913 0.23169366 0.43051607
#> [97] 0.99256600 0.80388327 0.32561005 0.00000000 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000
#>
#> $Time
#> 183 197 123 164 63 110 128 125 92 42 179 154 177
#> 9.24 21.60 13.00 23.60 22.77 17.56 20.35 15.65 22.92 12.43 18.63 12.63 12.53
#> 37 56 37.1 78 91 192 66 43 76 106 175 136 111
#> 12.52 12.21 12.52 23.88 5.33 16.44 22.13 12.10 19.22 16.67 21.91 21.83 17.45
#> 188 51 56.1 111.1 93 24 168 99 92.1 92.2 55 29 149
#> 16.16 18.23 12.21 17.45 10.33 23.89 23.72 21.19 22.92 22.92 19.34 15.45 8.37
#> 123.1 192.1 140 117 96 168.1 69 105 39 79 110.1 85 56.2
#> 13.00 16.44 12.68 17.46 14.54 23.72 23.23 19.75 15.59 16.23 17.56 16.44 12.21
#> 23 57 51.1 8 113 188.1 101 6 41 5 175.1 129 30
#> 16.92 14.46 18.23 18.43 22.86 16.16 9.97 15.64 18.02 16.43 21.91 23.41 17.43
#> 40 18 85.1 13 58 175.2 8.1 179.1 187 45 81 145 180
#> 18.00 15.21 16.44 14.34 19.34 21.91 18.43 18.63 9.92 17.42 14.06 10.07 14.82
#> 164.1 26 79.1 86 166 197.1 45.1 166.1 183.1 32 93.1 16 168.2
#> 23.60 15.77 16.23 23.81 19.98 21.60 17.42 19.98 9.24 20.90 10.33 8.71 23.72
#> 70 8.2 24.1 169 97 127 155 139 64 3 156 46 75
#> 7.38 18.43 23.89 22.41 19.14 3.53 13.08 21.49 24.00 24.00 24.00 24.00 24.00
#> 64.1 72 102 104 120 33 118 27 20 198 71 35 116
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72.1 182 186 83 35.1 109 141 1 54 104.1 176 62 191
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 48 83.1 98 118.1 48.1 9 126 9.1 64.2 65 65.1 53 132
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 7 9.2 7.1 87 138 3.1 72.2 20.1 17 191.1 161 80 28
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20.2 160 28.1 44 74 31 144 131 54.1 82 83.2 141.1 132.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1.1 185 151 67 118.2 193 112 162 151.1 74.1 103 38 33.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 200 11 131.1 196 185.1
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[39]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.0004039159 0.5317682623 0.8243209081
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.81606714 0.01860724 -0.29020873
#> grade_iii, Cure model
#> 0.99726508
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 110 17.56 1 65 0 1
#> 167 15.55 1 56 1 0
#> 4 17.64 1 NA 0 1
#> 26 15.77 1 49 0 1
#> 154 12.63 1 20 1 0
#> 179 18.63 1 42 0 0
#> 157 15.10 1 47 0 0
#> 170 19.54 1 43 0 1
#> 188 16.16 1 46 0 1
#> 167.1 15.55 1 56 1 0
#> 63 22.77 1 31 1 0
#> 175 21.91 1 43 0 0
#> 91 5.33 1 61 0 1
#> 159 10.55 1 50 0 1
#> 70 7.38 1 30 1 0
#> 24 23.89 1 38 0 0
#> 154.1 12.63 1 20 1 0
#> 42 12.43 1 49 0 1
#> 97 19.14 1 65 0 1
#> 76 19.22 1 54 0 1
#> 195 11.76 1 NA 1 0
#> 170.1 19.54 1 43 0 1
#> 177 12.53 1 75 0 0
#> 179.1 18.63 1 42 0 0
#> 60 13.15 1 38 1 0
#> 26.1 15.77 1 49 0 1
#> 93 10.33 1 52 0 1
#> 78 23.88 1 43 0 0
#> 52 10.42 1 52 0 1
#> 90 20.94 1 50 0 1
#> 30 17.43 1 78 0 0
#> 59 10.16 1 NA 1 0
#> 101 9.97 1 10 0 1
#> 85 16.44 1 36 0 0
#> 114 13.68 1 NA 0 0
#> 157.1 15.10 1 47 0 0
#> 113 22.86 1 34 0 0
#> 18 15.21 1 49 1 0
#> 39 15.59 1 37 0 1
#> 155 13.08 1 26 0 0
#> 30.1 17.43 1 78 0 0
#> 180 14.82 1 37 0 0
#> 187 9.92 1 39 1 0
#> 18.1 15.21 1 49 1 0
#> 13 14.34 1 54 0 1
#> 117 17.46 1 26 0 1
#> 169 22.41 1 46 0 0
#> 127 3.53 1 62 0 1
#> 129 23.41 1 53 1 0
#> 149 8.37 1 33 1 0
#> 101.1 9.97 1 10 0 1
#> 192 16.44 1 31 1 0
#> 105 19.75 1 60 0 0
#> 97.1 19.14 1 65 0 1
#> 30.2 17.43 1 78 0 0
#> 99 21.19 1 38 0 1
#> 45 17.42 1 54 0 1
#> 66 22.13 1 53 0 0
#> 167.2 15.55 1 56 1 0
#> 117.1 17.46 1 26 0 1
#> 197 21.60 1 69 1 0
#> 113.1 22.86 1 34 0 0
#> 153 21.33 1 55 1 0
#> 117.2 17.46 1 26 0 1
#> 91.1 5.33 1 61 0 1
#> 149.1 8.37 1 33 1 0
#> 199 19.81 1 NA 0 1
#> 129.1 23.41 1 53 1 0
#> 125 15.65 1 67 1 0
#> 26.2 15.77 1 49 0 1
#> 107 11.18 1 54 1 0
#> 136 21.83 1 43 0 1
#> 57 14.46 1 45 0 1
#> 29 15.45 1 68 1 0
#> 177.1 12.53 1 75 0 0
#> 52.1 10.42 1 52 0 1
#> 88 18.37 1 47 0 0
#> 197.1 21.60 1 69 1 0
#> 166 19.98 1 48 0 0
#> 184 17.77 1 38 0 0
#> 58 19.34 1 39 0 0
#> 13.1 14.34 1 54 0 1
#> 189 10.51 1 NA 1 0
#> 14 12.89 1 21 0 0
#> 177.2 12.53 1 75 0 0
#> 158 20.14 1 74 1 0
#> 15 22.68 1 48 0 0
#> 124 9.73 1 NA 1 0
#> 134 17.81 1 47 1 0
#> 52.2 10.42 1 52 0 1
#> 169.1 22.41 1 46 0 0
#> 49 12.19 1 48 1 0
#> 43 12.10 1 61 0 1
#> 128 20.35 1 35 0 1
#> 16 8.71 1 71 0 1
#> 15.1 22.68 1 48 0 0
#> 175.1 21.91 1 43 0 0
#> 10 10.53 1 34 0 0
#> 13.2 14.34 1 54 0 1
#> 14.1 12.89 1 21 0 0
#> 187.1 9.92 1 39 1 0
#> 171 16.57 1 41 0 1
#> 90.1 20.94 1 50 0 1
#> 58.1 19.34 1 39 0 0
#> 42.1 12.43 1 49 0 1
#> 29.1 15.45 1 68 1 0
#> 149.2 8.37 1 33 1 0
#> 50 10.02 1 NA 1 0
#> 150 20.33 1 48 0 0
#> 5 16.43 1 51 0 1
#> 171.1 16.57 1 41 0 1
#> 110.1 17.56 1 65 0 1
#> 137 24.00 0 45 1 0
#> 12 24.00 0 63 0 0
#> 102 24.00 0 49 0 0
#> 67 24.00 0 25 0 0
#> 98 24.00 0 34 1 0
#> 132 24.00 0 55 0 0
#> 185 24.00 0 44 1 0
#> 174 24.00 0 49 1 0
#> 173 24.00 0 19 0 1
#> 120 24.00 0 68 0 1
#> 71 24.00 0 51 0 0
#> 74 24.00 0 43 0 1
#> 115 24.00 0 NA 1 0
#> 47 24.00 0 38 0 1
#> 22 24.00 0 52 1 0
#> 74.1 24.00 0 43 0 1
#> 121 24.00 0 57 1 0
#> 38 24.00 0 31 1 0
#> 64 24.00 0 43 0 0
#> 72 24.00 0 40 0 1
#> 121.1 24.00 0 57 1 0
#> 94 24.00 0 51 0 1
#> 28 24.00 0 67 1 0
#> 131 24.00 0 66 0 0
#> 73 24.00 0 NA 0 1
#> 83 24.00 0 6 0 0
#> 103 24.00 0 56 1 0
#> 147 24.00 0 76 1 0
#> 20 24.00 0 46 1 0
#> 143 24.00 0 51 0 0
#> 152 24.00 0 36 0 1
#> 182 24.00 0 35 0 0
#> 112 24.00 0 61 0 0
#> 186 24.00 0 45 1 0
#> 165 24.00 0 47 0 0
#> 47.1 24.00 0 38 0 1
#> 116 24.00 0 58 0 1
#> 3 24.00 0 31 1 0
#> 7 24.00 0 37 1 0
#> 152.1 24.00 0 36 0 1
#> 126 24.00 0 48 0 0
#> 173.1 24.00 0 19 0 1
#> 21 24.00 0 47 0 0
#> 12.1 24.00 0 63 0 0
#> 120.1 24.00 0 68 0 1
#> 64.1 24.00 0 43 0 0
#> 21.1 24.00 0 47 0 0
#> 80 24.00 0 41 0 0
#> 1 24.00 0 23 1 0
#> 75 24.00 0 21 1 0
#> 147.1 24.00 0 76 1 0
#> 38.1 24.00 0 31 1 0
#> 75.1 24.00 0 21 1 0
#> 115.1 24.00 0 NA 1 0
#> 115.2 24.00 0 NA 1 0
#> 87 24.00 0 27 0 0
#> 2 24.00 0 9 0 0
#> 160 24.00 0 31 1 0
#> 35 24.00 0 51 0 0
#> 156 24.00 0 50 1 0
#> 62 24.00 0 71 0 0
#> 48 24.00 0 31 1 0
#> 48.1 24.00 0 31 1 0
#> 186.1 24.00 0 45 1 0
#> 185.1 24.00 0 44 1 0
#> 121.2 24.00 0 57 1 0
#> 151 24.00 0 42 0 0
#> 196 24.00 0 19 0 0
#> 156.1 24.00 0 50 1 0
#> 142 24.00 0 53 0 0
#> 94.1 24.00 0 51 0 1
#> 172 24.00 0 41 0 0
#> 103.1 24.00 0 56 1 0
#> 144 24.00 0 28 0 1
#> 182.1 24.00 0 35 0 0
#> 135 24.00 0 58 1 0
#> 142.1 24.00 0 53 0 0
#> 178 24.00 0 52 1 0
#> 67.1 24.00 0 25 0 0
#> 163 24.00 0 66 0 0
#> 185.2 24.00 0 44 1 0
#> 87.1 24.00 0 27 0 0
#> 3.1 24.00 0 31 1 0
#> 182.2 24.00 0 35 0 0
#> 138 24.00 0 44 1 0
#> 9 24.00 0 31 1 0
#> 98.1 24.00 0 34 1 0
#> 165.1 24.00 0 47 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.816 NA NA NA
#> 2 age, Cure model 0.0186 NA NA NA
#> 3 grade_ii, Cure model -0.290 NA NA NA
#> 4 grade_iii, Cure model 0.997 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.000404 NA NA NA
#> 2 grade_ii, Survival model 0.532 NA NA NA
#> 3 grade_iii, Survival model 0.824 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.81607 0.01861 -0.29021 0.99727
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 258.5
#> Residual Deviance: 243 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.81606714 0.01860724 -0.29020873 0.99726508
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.0004039159 0.5317682623 0.8243209081
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.53710764 0.70119843 0.66374451 0.82646159 0.48883685 0.75117964
#> [7] 0.41761123 0.65582326 0.70119843 0.13987697 0.23584647 0.98276447
#> [13] 0.89203057 0.97691017 0.01587298 0.82646159 0.85960109 0.46956170
#> [19] 0.45930358 0.41761123 0.83974337 0.48883685 0.79954749 0.66374451
#> [25] 0.92325118 0.04381979 0.90476319 0.33747170 0.58100447 0.92940445
#> [31] 0.63155148 0.75117964 0.10624395 0.73707900 0.69377070 0.80628908
#> [37] 0.58100447 0.76528527 0.94146790 0.73707900 0.77937878 0.55538730
#> [43] 0.18786128 0.99427079 0.07284486 0.95938117 0.92940445 0.63155148
#> [49] 0.40635276 0.46956170 0.58100447 0.32438471 0.60665689 0.21942540
#> [55] 0.70119843 0.55538730 0.28285916 0.10624395 0.31060546 0.55538730
#> [61] 0.98276447 0.95938117 0.07284486 0.68624250 0.66374451 0.88560797
#> [67] 0.26762519 0.77237186 0.72279569 0.83974337 0.90476319 0.50812488
#> [73] 0.28285916 0.39510177 0.52748533 0.43844957 0.77937878 0.81303126
#> [79] 0.83974337 0.38385695 0.15640674 0.51786571 0.90476319 0.18786128
#> [85] 0.87264195 0.87915424 0.36093641 0.95342786 0.15640674 0.23584647
#> [91] 0.89839657 0.77937878 0.81303126 0.94146790 0.61518109 0.33747170
#> [97] 0.43844957 0.85960109 0.72279569 0.95938117 0.37239328 0.64778174
#> [103] 0.61518109 0.53710764 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000
#>
#> $Time
#> 110 167 26 154 179 157 170 188 167.1 63 175 91 159
#> 17.56 15.55 15.77 12.63 18.63 15.10 19.54 16.16 15.55 22.77 21.91 5.33 10.55
#> 70 24 154.1 42 97 76 170.1 177 179.1 60 26.1 93 78
#> 7.38 23.89 12.63 12.43 19.14 19.22 19.54 12.53 18.63 13.15 15.77 10.33 23.88
#> 52 90 30 101 85 157.1 113 18 39 155 30.1 180 187
#> 10.42 20.94 17.43 9.97 16.44 15.10 22.86 15.21 15.59 13.08 17.43 14.82 9.92
#> 18.1 13 117 169 127 129 149 101.1 192 105 97.1 30.2 99
#> 15.21 14.34 17.46 22.41 3.53 23.41 8.37 9.97 16.44 19.75 19.14 17.43 21.19
#> 45 66 167.2 117.1 197 113.1 153 117.2 91.1 149.1 129.1 125 26.2
#> 17.42 22.13 15.55 17.46 21.60 22.86 21.33 17.46 5.33 8.37 23.41 15.65 15.77
#> 107 136 57 29 177.1 52.1 88 197.1 166 184 58 13.1 14
#> 11.18 21.83 14.46 15.45 12.53 10.42 18.37 21.60 19.98 17.77 19.34 14.34 12.89
#> 177.2 158 15 134 52.2 169.1 49 43 128 16 15.1 175.1 10
#> 12.53 20.14 22.68 17.81 10.42 22.41 12.19 12.10 20.35 8.71 22.68 21.91 10.53
#> 13.2 14.1 187.1 171 90.1 58.1 42.1 29.1 149.2 150 5 171.1 110.1
#> 14.34 12.89 9.92 16.57 20.94 19.34 12.43 15.45 8.37 20.33 16.43 16.57 17.56
#> 137 12 102 67 98 132 185 174 173 120 71 74 47
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 22 74.1 121 38 64 72 121.1 94 28 131 83 103 147
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20 143 152 182 112 186 165 47.1 116 3 7 152.1 126
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 173.1 21 12.1 120.1 64.1 21.1 80 1 75 147.1 38.1 75.1 87
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 2 160 35 156 62 48 48.1 186.1 185.1 121.2 151 196 156.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142 94.1 172 103.1 144 182.1 135 142.1 178 67.1 163 185.2 87.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3.1 182.2 138 9 98.1 165.1
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[40]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.007703846 0.475502587 0.762392404
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.355593318 0.008297693 -0.467045250
#> grade_iii, Cure model
#> 0.857123667
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 154 12.63 1 20 1 0
#> 13 14.34 1 54 0 1
#> 89 11.44 1 NA 0 0
#> 127 3.53 1 62 0 1
#> 13.1 14.34 1 54 0 1
#> 106 16.67 1 49 1 0
#> 101 9.97 1 10 0 1
#> 60 13.15 1 38 1 0
#> 170 19.54 1 43 0 1
#> 76 19.22 1 54 0 1
#> 8 18.43 1 32 0 0
#> 59 10.16 1 NA 1 0
#> 91 5.33 1 61 0 1
#> 56 12.21 1 60 0 0
#> 150 20.33 1 48 0 0
#> 43 12.10 1 61 0 1
#> 100 16.07 1 60 0 0
#> 58 19.34 1 39 0 0
#> 199 19.81 1 NA 0 1
#> 168 23.72 1 70 0 0
#> 15 22.68 1 48 0 0
#> 179 18.63 1 42 0 0
#> 184 17.77 1 38 0 0
#> 110 17.56 1 65 0 1
#> 63 22.77 1 31 1 0
#> 125 15.65 1 67 1 0
#> 68 20.62 1 44 0 0
#> 114 13.68 1 NA 0 0
#> 77 7.27 1 67 0 1
#> 6 15.64 1 39 0 0
#> 139 21.49 1 63 1 0
#> 175 21.91 1 43 0 0
#> 110.1 17.56 1 65 0 1
#> 77.1 7.27 1 67 0 1
#> 168.1 23.72 1 70 0 0
#> 150.1 20.33 1 48 0 0
#> 180 14.82 1 37 0 0
#> 179.1 18.63 1 42 0 0
#> 170.1 19.54 1 43 0 1
#> 18 15.21 1 49 1 0
#> 136 21.83 1 43 0 1
#> 117 17.46 1 26 0 1
#> 157 15.10 1 47 0 0
#> 50 10.02 1 NA 1 0
#> 170.2 19.54 1 43 0 1
#> 78 23.88 1 43 0 0
#> 55 19.34 1 69 0 1
#> 187 9.92 1 39 1 0
#> 150.2 20.33 1 48 0 0
#> 10 10.53 1 34 0 0
#> 16 8.71 1 71 0 1
#> 50.1 10.02 1 NA 1 0
#> 16.1 8.71 1 71 0 1
#> 16.2 8.71 1 71 0 1
#> 183 9.24 1 67 1 0
#> 107 11.18 1 54 1 0
#> 89.1 11.44 1 NA 0 0
#> 188 16.16 1 46 0 1
#> 101.1 9.97 1 10 0 1
#> 32 20.90 1 37 1 0
#> 195 11.76 1 NA 1 0
#> 133 14.65 1 57 0 0
#> 14 12.89 1 21 0 0
#> 13.2 14.34 1 54 0 1
#> 26 15.77 1 49 0 1
#> 70 7.38 1 30 1 0
#> 51 18.23 1 83 0 1
#> 170.3 19.54 1 43 0 1
#> 123 13.00 1 44 1 0
#> 43.1 12.10 1 61 0 1
#> 168.2 23.72 1 70 0 0
#> 101.2 9.97 1 10 0 1
#> 108 18.29 1 39 0 1
#> 52 10.42 1 52 0 1
#> 40 18.00 1 28 1 0
#> 63.1 22.77 1 31 1 0
#> 154.1 12.63 1 20 1 0
#> 63.2 22.77 1 31 1 0
#> 52.1 10.42 1 52 0 1
#> 171 16.57 1 41 0 1
#> 113 22.86 1 34 0 0
#> 99 21.19 1 38 0 1
#> 150.3 20.33 1 48 0 0
#> 184.1 17.77 1 38 0 0
#> 130 16.47 1 53 0 1
#> 57 14.46 1 45 0 1
#> 77.2 7.27 1 67 0 1
#> 129 23.41 1 53 1 0
#> 81 14.06 1 34 0 0
#> 96 14.54 1 33 0 1
#> 4 17.64 1 NA 0 1
#> 61 10.12 1 36 0 1
#> 157.1 15.10 1 47 0 0
#> 111 17.45 1 47 0 1
#> 164 23.60 1 76 0 1
#> 60.1 13.15 1 38 1 0
#> 70.1 7.38 1 30 1 0
#> 136.1 21.83 1 43 0 1
#> 93 10.33 1 52 0 1
#> 134 17.81 1 47 1 0
#> 180.1 14.82 1 37 0 0
#> 55.1 19.34 1 69 0 1
#> 127.1 3.53 1 62 0 1
#> 123.1 13.00 1 44 1 0
#> 145 10.07 1 65 1 0
#> 175.1 21.91 1 43 0 0
#> 158 20.14 1 74 1 0
#> 150.4 20.33 1 48 0 0
#> 199.1 19.81 1 NA 0 1
#> 88 18.37 1 47 0 0
#> 30 17.43 1 78 0 0
#> 92 22.92 1 47 0 1
#> 7 24.00 0 37 1 0
#> 162 24.00 0 51 0 0
#> 95 24.00 0 68 0 1
#> 74 24.00 0 43 0 1
#> 178 24.00 0 52 1 0
#> 119 24.00 0 17 0 0
#> 11 24.00 0 42 0 1
#> 148 24.00 0 61 1 0
#> 135 24.00 0 58 1 0
#> 148.1 24.00 0 61 1 0
#> 143 24.00 0 51 0 0
#> 196 24.00 0 19 0 0
#> 64 24.00 0 43 0 0
#> 160 24.00 0 31 1 0
#> 151 24.00 0 42 0 0
#> 147 24.00 0 76 1 0
#> 98 24.00 0 34 1 0
#> 22 24.00 0 52 1 0
#> 141 24.00 0 44 1 0
#> 162.1 24.00 0 51 0 0
#> 156 24.00 0 50 1 0
#> 144 24.00 0 28 0 1
#> 33 24.00 0 53 0 0
#> 62 24.00 0 71 0 0
#> 135.1 24.00 0 58 1 0
#> 143.1 24.00 0 51 0 0
#> 64.1 24.00 0 43 0 0
#> 54 24.00 0 53 1 0
#> 156.1 24.00 0 50 1 0
#> 103 24.00 0 56 1 0
#> 17 24.00 0 38 0 1
#> 83 24.00 0 6 0 0
#> 146 24.00 0 63 1 0
#> 1 24.00 0 23 1 0
#> 71 24.00 0 51 0 0
#> 34 24.00 0 36 0 0
#> 2 24.00 0 9 0 0
#> 71.1 24.00 0 51 0 0
#> 48 24.00 0 31 1 0
#> 28 24.00 0 67 1 0
#> 3 24.00 0 31 1 0
#> 131 24.00 0 66 0 0
#> 172 24.00 0 41 0 0
#> 82 24.00 0 34 0 0
#> 72 24.00 0 40 0 1
#> 148.2 24.00 0 61 1 0
#> 1.1 24.00 0 23 1 0
#> 185 24.00 0 44 1 0
#> 31 24.00 0 36 0 1
#> 146.1 24.00 0 63 1 0
#> 64.2 24.00 0 43 0 0
#> 87 24.00 0 27 0 0
#> 120 24.00 0 68 0 1
#> 2.1 24.00 0 9 0 0
#> 38 24.00 0 31 1 0
#> 172.1 24.00 0 41 0 0
#> 102 24.00 0 49 0 0
#> 65 24.00 0 57 1 0
#> 198 24.00 0 66 0 1
#> 22.1 24.00 0 52 1 0
#> 19 24.00 0 57 0 1
#> 119.1 24.00 0 17 0 0
#> 47 24.00 0 38 0 1
#> 148.3 24.00 0 61 1 0
#> 135.2 24.00 0 58 1 0
#> 54.1 24.00 0 53 1 0
#> 75 24.00 0 21 1 0
#> 112 24.00 0 61 0 0
#> 119.2 24.00 0 17 0 0
#> 156.2 24.00 0 50 1 0
#> 7.1 24.00 0 37 1 0
#> 146.2 24.00 0 63 1 0
#> 116 24.00 0 58 0 1
#> 109 24.00 0 48 0 0
#> 44 24.00 0 56 0 0
#> 33.1 24.00 0 53 0 0
#> 161 24.00 0 45 0 0
#> 11.1 24.00 0 42 0 1
#> 137 24.00 0 45 1 0
#> 84 24.00 0 39 0 1
#> 19.1 24.00 0 57 0 1
#> 119.3 24.00 0 17 0 0
#> 11.2 24.00 0 42 0 1
#> 147.1 24.00 0 76 1 0
#> 120.1 24.00 0 68 0 1
#> 75.1 24.00 0 21 1 0
#> 67 24.00 0 25 0 0
#> 17.1 24.00 0 38 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.356 NA NA NA
#> 2 age, Cure model 0.00830 NA NA NA
#> 3 grade_ii, Cure model -0.467 NA NA NA
#> 4 grade_iii, Cure model 0.857 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00770 NA NA NA
#> 2 grade_ii, Survival model 0.476 NA NA NA
#> 3 grade_iii, Survival model 0.762 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.355593 0.008298 -0.467045 0.857124
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 262.4
#> Residual Deviance: 247.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.355593318 0.008297693 -0.467045250 0.857123667
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.007703846 0.475502587 0.762392404
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.751135342 0.666972386 0.982970818 0.666972386 0.512842406 0.861629199
#> [7] 0.704381510 0.284023832 0.352641488 0.382716176 0.974369728 0.769639964
#> [13] 0.221454458 0.778990427 0.551557252 0.323100545 0.012672452 0.124139943
#> [19] 0.362657848 0.443587154 0.463630105 0.094016023 0.570706873 0.210916251
#> [25] 0.948717319 0.580249695 0.179161887 0.135433946 0.463630105 0.948717319
#> [31] 0.012672452 0.221454458 0.618568301 0.362657848 0.284023832 0.589833423
#> [37] 0.158107865 0.483417404 0.599401145 0.284023832 0.003147792 0.323100545
#> [43] 0.887821827 0.221454458 0.806696602 0.905428168 0.905428168 0.905428168
#> [49] 0.896623276 0.797429665 0.542005716 0.861629199 0.200527351 0.637883936
#> [55] 0.741737028 0.666972386 0.561170407 0.931406456 0.413397177 0.284023832
#> [61] 0.723094543 0.778990427 0.012672452 0.861629199 0.403244568 0.815988135
#> [67] 0.423517278 0.094016023 0.751135342 0.094016023 0.815988135 0.522656835
#> [73] 0.081487778 0.190024437 0.221454458 0.443587154 0.532368620 0.657357240
#> [79] 0.948717319 0.056168904 0.694911237 0.647669052 0.843439889 0.599401145
#> [85] 0.493260881 0.042743518 0.704381510 0.931406456 0.158107865 0.834284828
#> [91] 0.433566158 0.618568301 0.323100545 0.982970818 0.723094543 0.852533334
#> [97] 0.135433946 0.272832049 0.221454458 0.392939644 0.503008604 0.069390841
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 154 13 127 13.1 106 101 60 170 76 8 91 56 150
#> 12.63 14.34 3.53 14.34 16.67 9.97 13.15 19.54 19.22 18.43 5.33 12.21 20.33
#> 43 100 58 168 15 179 184 110 63 125 68 77 6
#> 12.10 16.07 19.34 23.72 22.68 18.63 17.77 17.56 22.77 15.65 20.62 7.27 15.64
#> 139 175 110.1 77.1 168.1 150.1 180 179.1 170.1 18 136 117 157
#> 21.49 21.91 17.56 7.27 23.72 20.33 14.82 18.63 19.54 15.21 21.83 17.46 15.10
#> 170.2 78 55 187 150.2 10 16 16.1 16.2 183 107 188 101.1
#> 19.54 23.88 19.34 9.92 20.33 10.53 8.71 8.71 8.71 9.24 11.18 16.16 9.97
#> 32 133 14 13.2 26 70 51 170.3 123 43.1 168.2 101.2 108
#> 20.90 14.65 12.89 14.34 15.77 7.38 18.23 19.54 13.00 12.10 23.72 9.97 18.29
#> 52 40 63.1 154.1 63.2 52.1 171 113 99 150.3 184.1 130 57
#> 10.42 18.00 22.77 12.63 22.77 10.42 16.57 22.86 21.19 20.33 17.77 16.47 14.46
#> 77.2 129 81 96 61 157.1 111 164 60.1 70.1 136.1 93 134
#> 7.27 23.41 14.06 14.54 10.12 15.10 17.45 23.60 13.15 7.38 21.83 10.33 17.81
#> 180.1 55.1 127.1 123.1 145 175.1 158 150.4 88 30 92 7 162
#> 14.82 19.34 3.53 13.00 10.07 21.91 20.14 20.33 18.37 17.43 22.92 24.00 24.00
#> 95 74 178 119 11 148 135 148.1 143 196 64 160 151
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 147 98 22 141 162.1 156 144 33 62 135.1 143.1 64.1 54
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156.1 103 17 83 146 1 71 34 2 71.1 48 28 3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131 172 82 72 148.2 1.1 185 31 146.1 64.2 87 120 2.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 38 172.1 102 65 198 22.1 19 119.1 47 148.3 135.2 54.1 75
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 112 119.2 156.2 7.1 146.2 116 109 44 33.1 161 11.1 137 84
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 19.1 119.3 11.2 147.1 120.1 75.1 67 17.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[41]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.002470872 0.235502175 0.485429524
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.488953574 0.009047344 0.122071162
#> grade_iii, Cure model
#> 0.700672893
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 81 14.06 1 34 0 0
#> 39 15.59 1 37 0 1
#> 14 12.89 1 21 0 0
#> 125 15.65 1 67 1 0
#> 111 17.45 1 47 0 1
#> 153 21.33 1 55 1 0
#> 105 19.75 1 60 0 0
#> 197 21.60 1 69 1 0
#> 140 12.68 1 59 1 0
#> 42 12.43 1 49 0 1
#> 23 16.92 1 61 0 0
#> 61 10.12 1 36 0 1
#> 41 18.02 1 40 1 0
#> 43 12.10 1 61 0 1
#> 127 3.53 1 62 0 1
#> 134 17.81 1 47 1 0
#> 36 21.19 1 48 0 1
#> 16 8.71 1 71 0 1
#> 25 6.32 1 34 1 0
#> 157 15.10 1 47 0 0
#> 79 16.23 1 54 1 0
#> 184 17.77 1 38 0 0
#> 92 22.92 1 47 0 1
#> 167 15.55 1 56 1 0
#> 26 15.77 1 49 0 1
#> 43.1 12.10 1 61 0 1
#> 52 10.42 1 52 0 1
#> 197.1 21.60 1 69 1 0
#> 129 23.41 1 53 1 0
#> 45 17.42 1 54 0 1
#> 199 19.81 1 NA 0 1
#> 175 21.91 1 43 0 0
#> 180 14.82 1 37 0 0
#> 192 16.44 1 31 1 0
#> 26.1 15.77 1 49 0 1
#> 39.1 15.59 1 37 0 1
#> 192.1 16.44 1 31 1 0
#> 105.1 19.75 1 60 0 0
#> 192.2 16.44 1 31 1 0
#> 124 9.73 1 NA 1 0
#> 37 12.52 1 57 1 0
#> 108 18.29 1 39 0 1
#> 40 18.00 1 28 1 0
#> 49 12.19 1 48 1 0
#> 97 19.14 1 65 0 1
#> 32 20.90 1 37 1 0
#> 100 16.07 1 60 0 0
#> 61.1 10.12 1 36 0 1
#> 195 11.76 1 NA 1 0
#> 158 20.14 1 74 1 0
#> 13 14.34 1 54 0 1
#> 39.2 15.59 1 37 0 1
#> 56 12.21 1 60 0 0
#> 96 14.54 1 33 0 1
#> 188 16.16 1 46 0 1
#> 89 11.44 1 NA 0 0
#> 24 23.89 1 38 0 0
#> 29 15.45 1 68 1 0
#> 188.1 16.16 1 46 0 1
#> 114 13.68 1 NA 0 0
#> 18 15.21 1 49 1 0
#> 101 9.97 1 10 0 1
#> 111.1 17.45 1 47 0 1
#> 159 10.55 1 50 0 1
#> 180.1 14.82 1 37 0 0
#> 57 14.46 1 45 0 1
#> 153.1 21.33 1 55 1 0
#> 91 5.33 1 61 0 1
#> 129.1 23.41 1 53 1 0
#> 110 17.56 1 65 0 1
#> 181 16.46 1 45 0 1
#> 175.1 21.91 1 43 0 0
#> 37.1 12.52 1 57 1 0
#> 114.1 13.68 1 NA 0 0
#> 99 21.19 1 38 0 1
#> 61.2 10.12 1 36 0 1
#> 45.1 17.42 1 54 0 1
#> 26.2 15.77 1 49 0 1
#> 58 19.34 1 39 0 0
#> 157.1 15.10 1 47 0 0
#> 177 12.53 1 75 0 0
#> 77 7.27 1 67 0 1
#> 136 21.83 1 43 0 1
#> 68 20.62 1 44 0 0
#> 29.1 15.45 1 68 1 0
#> 61.3 10.12 1 36 0 1
#> 139 21.49 1 63 1 0
#> 111.2 17.45 1 47 0 1
#> 181.1 16.46 1 45 0 1
#> 164 23.60 1 76 0 1
#> 101.1 9.97 1 10 0 1
#> 157.2 15.10 1 47 0 0
#> 190 20.81 1 42 1 0
#> 69 23.23 1 25 0 1
#> 150 20.33 1 48 0 0
#> 157.3 15.10 1 47 0 0
#> 194 22.40 1 38 0 1
#> 149 8.37 1 33 1 0
#> 159.1 10.55 1 50 0 1
#> 111.3 17.45 1 47 0 1
#> 51 18.23 1 83 0 1
#> 24.1 23.89 1 38 0 0
#> 105.2 19.75 1 60 0 0
#> 70 7.38 1 30 1 0
#> 43.2 12.10 1 61 0 1
#> 30 17.43 1 78 0 0
#> 177.1 12.53 1 75 0 0
#> 18.1 15.21 1 49 1 0
#> 159.2 10.55 1 50 0 1
#> 187 9.92 1 39 1 0
#> 195.1 11.76 1 NA 1 0
#> 113 22.86 1 34 0 0
#> 72 24.00 0 40 0 1
#> 182 24.00 0 35 0 0
#> 38 24.00 0 31 1 0
#> 109 24.00 0 48 0 0
#> 193 24.00 0 45 0 1
#> 48 24.00 0 31 1 0
#> 152 24.00 0 36 0 1
#> 152.1 24.00 0 36 0 1
#> 198 24.00 0 66 0 1
#> 176 24.00 0 43 0 1
#> 147 24.00 0 76 1 0
#> 174 24.00 0 49 1 0
#> 198.1 24.00 0 66 0 1
#> 27 24.00 0 63 1 0
#> 118 24.00 0 44 1 0
#> 83 24.00 0 6 0 0
#> 135 24.00 0 58 1 0
#> 53 24.00 0 32 0 1
#> 62 24.00 0 71 0 0
#> 17 24.00 0 38 0 1
#> 191 24.00 0 60 0 1
#> 115 24.00 0 NA 1 0
#> 121 24.00 0 57 1 0
#> 162 24.00 0 51 0 0
#> 95 24.00 0 68 0 1
#> 62.1 24.00 0 71 0 0
#> 72.1 24.00 0 40 0 1
#> 83.1 24.00 0 6 0 0
#> 200 24.00 0 64 0 0
#> 104 24.00 0 50 1 0
#> 73 24.00 0 NA 0 1
#> 191.1 24.00 0 60 0 1
#> 116 24.00 0 58 0 1
#> 137 24.00 0 45 1 0
#> 87 24.00 0 27 0 0
#> 122 24.00 0 66 0 0
#> 34 24.00 0 36 0 0
#> 104.1 24.00 0 50 1 0
#> 148 24.00 0 61 1 0
#> 87.1 24.00 0 27 0 0
#> 75 24.00 0 21 1 0
#> 160 24.00 0 31 1 0
#> 67 24.00 0 25 0 0
#> 142 24.00 0 53 0 0
#> 174.1 24.00 0 49 1 0
#> 19 24.00 0 57 0 1
#> 115.1 24.00 0 NA 1 0
#> 47 24.00 0 38 0 1
#> 185 24.00 0 44 1 0
#> 19.1 24.00 0 57 0 1
#> 182.1 24.00 0 35 0 0
#> 135.1 24.00 0 58 1 0
#> 104.2 24.00 0 50 1 0
#> 131 24.00 0 66 0 0
#> 64 24.00 0 43 0 0
#> 35 24.00 0 51 0 0
#> 64.1 24.00 0 43 0 0
#> 1 24.00 0 23 1 0
#> 191.2 24.00 0 60 0 1
#> 146 24.00 0 63 1 0
#> 174.2 24.00 0 49 1 0
#> 116.1 24.00 0 58 0 1
#> 135.2 24.00 0 58 1 0
#> 48.1 24.00 0 31 1 0
#> 118.1 24.00 0 44 1 0
#> 160.1 24.00 0 31 1 0
#> 176.1 24.00 0 43 0 1
#> 151 24.00 0 42 0 0
#> 102 24.00 0 49 0 0
#> 94 24.00 0 51 0 1
#> 142.1 24.00 0 53 0 0
#> 9 24.00 0 31 1 0
#> 176.2 24.00 0 43 0 1
#> 132 24.00 0 55 0 0
#> 22 24.00 0 52 1 0
#> 12 24.00 0 63 0 0
#> 116.2 24.00 0 58 0 1
#> 64.2 24.00 0 43 0 0
#> 3 24.00 0 31 1 0
#> 151.1 24.00 0 42 0 0
#> 104.3 24.00 0 50 1 0
#> 83.2 24.00 0 6 0 0
#> 116.3 24.00 0 58 0 1
#> 115.2 24.00 0 NA 1 0
#> 115.3 24.00 0 NA 1 0
#> 95.1 24.00 0 68 0 1
#> 73.1 24.00 0 NA 0 1
#> 67.1 24.00 0 25 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.489 NA NA NA
#> 2 age, Cure model 0.00905 NA NA NA
#> 3 grade_ii, Cure model 0.122 NA NA NA
#> 4 grade_iii, Cure model 0.701 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00247 NA NA NA
#> 2 grade_ii, Survival model 0.236 NA NA NA
#> 3 grade_iii, Survival model 0.485 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.488954 0.009047 0.122071 0.700673
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 256.4
#> Residual Deviance: 251 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.488953574 0.009047344 0.122071162 0.700672893
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.002470872 0.235502175 0.485429524
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.74690393 0.60231945 0.75538709 0.59351790 0.41197194 0.19672173
#> [7] 0.29014339 0.16401770 0.76387507 0.80617372 0.47689844 0.88904890
#> [13] 0.36182797 0.83154156 0.99216346 0.38197494 0.21803002 0.94472358
#> [19] 0.97641642 0.67046844 0.53153471 0.39199037 0.09455156 0.62780862
#> [25] 0.56747533 0.83154156 0.88084010 0.16401770 0.05644886 0.45833945
#> [31] 0.13024316 0.70422701 0.50459138 0.56747533 0.60231945 0.50459138
#> [37] 0.29014339 0.50459138 0.78928194 0.34145335 0.37192613 0.82308877
#> [43] 0.33107032 0.23842142 0.55847382 0.88904890 0.27978394 0.73842852
#> [49] 0.60231945 0.81462519 0.72134989 0.54065515 0.01372447 0.63641062
#> [55] 0.54065515 0.65346642 0.92086838 0.41197194 0.85634547 0.70422701
#> [61] 0.72991188 0.19672173 0.98430246 0.05644886 0.40202879 0.48629586
#> [67] 0.13024316 0.78928194 0.21803002 0.88904890 0.45833945 0.56747533
#> [73] 0.32056084 0.67046844 0.77235421 0.96851994 0.15272655 0.25906816
#> [79] 0.63641062 0.88904890 0.18563417 0.41197194 0.48629586 0.04116642
#> [85] 0.92086838 0.67046844 0.24877492 0.08182153 0.26940376 0.67046844
#> [91] 0.11868503 0.95266685 0.85634547 0.41197194 0.35168839 0.01372447
#> [97] 0.29014339 0.96059913 0.83154156 0.44879946 0.77235421 0.65346642
#> [103] 0.85634547 0.93675595 0.10656257 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000
#>
#> $Time
#> 81 39 14 125 111 153 105 197 140 42 23 61 41
#> 14.06 15.59 12.89 15.65 17.45 21.33 19.75 21.60 12.68 12.43 16.92 10.12 18.02
#> 43 127 134 36 16 25 157 79 184 92 167 26 43.1
#> 12.10 3.53 17.81 21.19 8.71 6.32 15.10 16.23 17.77 22.92 15.55 15.77 12.10
#> 52 197.1 129 45 175 180 192 26.1 39.1 192.1 105.1 192.2 37
#> 10.42 21.60 23.41 17.42 21.91 14.82 16.44 15.77 15.59 16.44 19.75 16.44 12.52
#> 108 40 49 97 32 100 61.1 158 13 39.2 56 96 188
#> 18.29 18.00 12.19 19.14 20.90 16.07 10.12 20.14 14.34 15.59 12.21 14.54 16.16
#> 24 29 188.1 18 101 111.1 159 180.1 57 153.1 91 129.1 110
#> 23.89 15.45 16.16 15.21 9.97 17.45 10.55 14.82 14.46 21.33 5.33 23.41 17.56
#> 181 175.1 37.1 99 61.2 45.1 26.2 58 157.1 177 77 136 68
#> 16.46 21.91 12.52 21.19 10.12 17.42 15.77 19.34 15.10 12.53 7.27 21.83 20.62
#> 29.1 61.3 139 111.2 181.1 164 101.1 157.2 190 69 150 157.3 194
#> 15.45 10.12 21.49 17.45 16.46 23.60 9.97 15.10 20.81 23.23 20.33 15.10 22.40
#> 149 159.1 111.3 51 24.1 105.2 70 43.2 30 177.1 18.1 159.2 187
#> 8.37 10.55 17.45 18.23 23.89 19.75 7.38 12.10 17.43 12.53 15.21 10.55 9.92
#> 113 72 182 38 109 193 48 152 152.1 198 176 147 174
#> 22.86 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 198.1 27 118 83 135 53 62 17 191 121 162 95 62.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72.1 83.1 200 104 191.1 116 137 87 122 34 104.1 148 87.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75 160 67 142 174.1 19 47 185 19.1 182.1 135.1 104.2 131
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64 35 64.1 1 191.2 146 174.2 116.1 135.2 48.1 118.1 160.1 176.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 151 102 94 142.1 9 176.2 132 22 12 116.2 64.2 3 151.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 104.3 83.2 116.3 95.1 67.1
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[42]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01305825 0.70891359 0.32371763
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.93029623 0.02386095 -0.17772699
#> grade_iii, Cure model
#> -0.03988936
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 158 20.14 1 74 1 0
#> 86 23.81 1 58 0 1
#> 130 16.47 1 53 0 1
#> 50 10.02 1 NA 1 0
#> 90 20.94 1 50 0 1
#> 133 14.65 1 57 0 0
#> 49 12.19 1 48 1 0
#> 140 12.68 1 59 1 0
#> 6 15.64 1 39 0 0
#> 139 21.49 1 63 1 0
#> 124 9.73 1 NA 1 0
#> 150 20.33 1 48 0 0
#> 23 16.92 1 61 0 0
#> 29 15.45 1 68 1 0
#> 129 23.41 1 53 1 0
#> 154 12.63 1 20 1 0
#> 145 10.07 1 65 1 0
#> 110 17.56 1 65 0 1
#> 88 18.37 1 47 0 0
#> 127 3.53 1 62 0 1
#> 139.1 21.49 1 63 1 0
#> 107 11.18 1 54 1 0
#> 55 19.34 1 69 0 1
#> 93 10.33 1 52 0 1
#> 188 16.16 1 46 0 1
#> 129.1 23.41 1 53 1 0
#> 40 18.00 1 28 1 0
#> 42 12.43 1 49 0 1
#> 8 18.43 1 32 0 0
#> 23.1 16.92 1 61 0 0
#> 78 23.88 1 43 0 0
#> 114 13.68 1 NA 0 0
#> 145.1 10.07 1 65 1 0
#> 50.1 10.02 1 NA 1 0
#> 100 16.07 1 60 0 0
#> 78.1 23.88 1 43 0 0
#> 110.1 17.56 1 65 0 1
#> 99 21.19 1 38 0 1
#> 85 16.44 1 36 0 0
#> 16 8.71 1 71 0 1
#> 96 14.54 1 33 0 1
#> 29.1 15.45 1 68 1 0
#> 197 21.60 1 69 1 0
#> 29.2 15.45 1 68 1 0
#> 29.3 15.45 1 68 1 0
#> 177 12.53 1 75 0 0
#> 6.1 15.64 1 39 0 0
#> 85.1 16.44 1 36 0 0
#> 76 19.22 1 54 0 1
#> 59 10.16 1 NA 1 0
#> 145.2 10.07 1 65 1 0
#> 181 16.46 1 45 0 1
#> 13 14.34 1 54 0 1
#> 18 15.21 1 49 1 0
#> 29.4 15.45 1 68 1 0
#> 175 21.91 1 43 0 0
#> 175.1 21.91 1 43 0 0
#> 30 17.43 1 78 0 0
#> 129.2 23.41 1 53 1 0
#> 187 9.92 1 39 1 0
#> 150.1 20.33 1 48 0 0
#> 15 22.68 1 48 0 0
#> 40.1 18.00 1 28 1 0
#> 188.1 16.16 1 46 0 1
#> 70 7.38 1 30 1 0
#> 197.1 21.60 1 69 1 0
#> 68 20.62 1 44 0 0
#> 66 22.13 1 53 0 0
#> 61 10.12 1 36 0 1
#> 70.1 7.38 1 30 1 0
#> 180 14.82 1 37 0 0
#> 166 19.98 1 48 0 0
#> 150.2 20.33 1 48 0 0
#> 168 23.72 1 70 0 0
#> 124.1 9.73 1 NA 1 0
#> 145.3 10.07 1 65 1 0
#> 23.2 16.92 1 61 0 0
#> 18.1 15.21 1 49 1 0
#> 30.1 17.43 1 78 0 0
#> 195 11.76 1 NA 1 0
#> 91 5.33 1 61 0 1
#> 8.1 18.43 1 32 0 0
#> 128 20.35 1 35 0 1
#> 66.1 22.13 1 53 0 0
#> 79 16.23 1 54 1 0
#> 168.1 23.72 1 70 0 0
#> 10 10.53 1 34 0 0
#> 29.5 15.45 1 68 1 0
#> 81 14.06 1 34 0 0
#> 189 10.51 1 NA 1 0
#> 136 21.83 1 43 0 1
#> 5 16.43 1 51 0 1
#> 61.1 10.12 1 36 0 1
#> 136.1 21.83 1 43 0 1
#> 57 14.46 1 45 0 1
#> 4 17.64 1 NA 0 1
#> 140.1 12.68 1 59 1 0
#> 58 19.34 1 39 0 0
#> 167 15.55 1 56 1 0
#> 99.1 21.19 1 38 0 1
#> 171 16.57 1 41 0 1
#> 52 10.42 1 52 0 1
#> 167.1 15.55 1 56 1 0
#> 189.1 10.51 1 NA 1 0
#> 149 8.37 1 33 1 0
#> 180.1 14.82 1 37 0 0
#> 128.1 20.35 1 35 0 1
#> 164 23.60 1 76 0 1
#> 10.1 10.53 1 34 0 0
#> 58.1 19.34 1 39 0 0
#> 26 15.77 1 49 0 1
#> 86.1 23.81 1 58 0 1
#> 122 24.00 0 66 0 0
#> 165 24.00 0 47 0 0
#> 48 24.00 0 31 1 0
#> 73 24.00 0 NA 0 1
#> 103 24.00 0 56 1 0
#> 64 24.00 0 43 0 0
#> 138 24.00 0 44 1 0
#> 27 24.00 0 63 1 0
#> 27.1 24.00 0 63 1 0
#> 141 24.00 0 44 1 0
#> 72 24.00 0 40 0 1
#> 163 24.00 0 66 0 0
#> 34 24.00 0 36 0 0
#> 120 24.00 0 68 0 1
#> 173 24.00 0 19 0 1
#> 19 24.00 0 57 0 1
#> 31 24.00 0 36 0 1
#> 98 24.00 0 34 1 0
#> 67 24.00 0 25 0 0
#> 141.1 24.00 0 44 1 0
#> 74 24.00 0 43 0 1
#> 21 24.00 0 47 0 0
#> 84 24.00 0 39 0 1
#> 186 24.00 0 45 1 0
#> 132 24.00 0 55 0 0
#> 173.1 24.00 0 19 0 1
#> 98.1 24.00 0 34 1 0
#> 71 24.00 0 51 0 0
#> 147 24.00 0 76 1 0
#> 21.1 24.00 0 47 0 0
#> 160 24.00 0 31 1 0
#> 193 24.00 0 45 0 1
#> 109 24.00 0 48 0 0
#> 135 24.00 0 58 1 0
#> 71.1 24.00 0 51 0 0
#> 21.2 24.00 0 47 0 0
#> 20 24.00 0 46 1 0
#> 53 24.00 0 32 0 1
#> 120.1 24.00 0 68 0 1
#> 48.1 24.00 0 31 1 0
#> 35 24.00 0 51 0 0
#> 196 24.00 0 19 0 0
#> 118 24.00 0 44 1 0
#> 47 24.00 0 38 0 1
#> 118.1 24.00 0 44 1 0
#> 74.1 24.00 0 43 0 1
#> 200 24.00 0 64 0 0
#> 172 24.00 0 41 0 0
#> 74.2 24.00 0 43 0 1
#> 200.1 24.00 0 64 0 0
#> 83 24.00 0 6 0 0
#> 12 24.00 0 63 0 0
#> 146 24.00 0 63 1 0
#> 95 24.00 0 68 0 1
#> 87 24.00 0 27 0 0
#> 80 24.00 0 41 0 0
#> 112 24.00 0 61 0 0
#> 156 24.00 0 50 1 0
#> 31.1 24.00 0 36 0 1
#> 3 24.00 0 31 1 0
#> 98.2 24.00 0 34 1 0
#> 122.1 24.00 0 66 0 0
#> 94 24.00 0 51 0 1
#> 95.1 24.00 0 68 0 1
#> 47.1 24.00 0 38 0 1
#> 148 24.00 0 61 1 0
#> 84.1 24.00 0 39 0 1
#> 75 24.00 0 21 1 0
#> 191 24.00 0 60 0 1
#> 84.2 24.00 0 39 0 1
#> 182 24.00 0 35 0 0
#> 87.1 24.00 0 27 0 0
#> 160.1 24.00 0 31 1 0
#> 109.1 24.00 0 48 0 0
#> 27.2 24.00 0 63 1 0
#> 144 24.00 0 28 0 1
#> 31.2 24.00 0 36 0 1
#> 67.1 24.00 0 25 0 0
#> 62 24.00 0 71 0 0
#> 95.2 24.00 0 68 0 1
#> 147.1 24.00 0 76 1 0
#> 146.1 24.00 0 63 1 0
#> 83.1 24.00 0 6 0 0
#> 191.1 24.00 0 60 0 1
#> 72.1 24.00 0 40 0 1
#> 121 24.00 0 57 1 0
#> 147.2 24.00 0 76 1 0
#> 118.2 24.00 0 44 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.930 NA NA NA
#> 2 age, Cure model 0.0239 NA NA NA
#> 3 grade_ii, Cure model -0.178 NA NA NA
#> 4 grade_iii, Cure model -0.0399 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0131 NA NA NA
#> 2 grade_ii, Survival model 0.709 NA NA NA
#> 3 grade_iii, Survival model 0.324 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.93030 0.02386 -0.17773 -0.03989
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.8
#> Residual Deviance: 255.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.93029623 0.02386095 -0.17772699 -0.03988936
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01305825 0.70891359 0.32371763
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.1805655181 0.0044737818 0.3613359827 0.1253748458 0.6348342473
#> [6] 0.7584888930 0.6963999867 0.4725403124 0.0965077525 0.1563232002
#> [11] 0.3197280448 0.5190715124 0.0246072262 0.7211231804 0.8596154748
#> [16] 0.2807643284 0.2524635964 0.9871056424 0.0965077525 0.7710080645
#> [21] 0.1978766087 0.8213686773 0.4271967955 0.0246072262 0.2622022175
#> [26] 0.7459520171 0.2336877351 0.3197280448 0.0007748585 0.8596154748
#> [31] 0.4495306864 0.0007748585 0.2807643284 0.1107912305 0.3829804041
#> [36] 0.9230562009 0.6470519677 0.5190715124 0.0824513265 0.5190715124
#> [41] 0.5190715124 0.7334719945 0.4725403124 0.3829804041 0.2243648265
#> [46] 0.8596154748 0.3721216834 0.6715873680 0.5872679314 0.5190715124
#> [51] 0.0557165999 0.0557165999 0.2998419304 0.0246072262 0.9101825388
#> [56] 0.1563232002 0.0382478040 0.2622022175 0.4271967955 0.9489100435
#> [61] 0.0824513265 0.1330206965 0.0438333266 0.8341477025 0.9489100435
#> [66] 0.6108736668 0.1891288181 0.1563232002 0.0101647651 0.8596154748
#> [71] 0.3197280448 0.5872679314 0.2998419304 0.9742757853 0.2336877351
#> [76] 0.1408636416 0.0438333266 0.4160232927 0.0101647651 0.7835264732
#> [81] 0.5190715124 0.6839533350 0.0688060364 0.4048486750 0.8341477025
#> [86] 0.0688060364 0.6592931916 0.6963999867 0.1978766087 0.4957937501
#> [91] 0.1107912305 0.3506485986 0.8086488353 0.4957937501 0.9360117272
#> [96] 0.6108736668 0.1408636416 0.0188488537 0.7835264732 0.1978766087
#> [101] 0.4609965841 0.0044737818 0.0000000000 0.0000000000 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#>
#> $Time
#> 158 86 130 90 133 49 140 6 139 150 23 29 129
#> 20.14 23.81 16.47 20.94 14.65 12.19 12.68 15.64 21.49 20.33 16.92 15.45 23.41
#> 154 145 110 88 127 139.1 107 55 93 188 129.1 40 42
#> 12.63 10.07 17.56 18.37 3.53 21.49 11.18 19.34 10.33 16.16 23.41 18.00 12.43
#> 8 23.1 78 145.1 100 78.1 110.1 99 85 16 96 29.1 197
#> 18.43 16.92 23.88 10.07 16.07 23.88 17.56 21.19 16.44 8.71 14.54 15.45 21.60
#> 29.2 29.3 177 6.1 85.1 76 145.2 181 13 18 29.4 175 175.1
#> 15.45 15.45 12.53 15.64 16.44 19.22 10.07 16.46 14.34 15.21 15.45 21.91 21.91
#> 30 129.2 187 150.1 15 40.1 188.1 70 197.1 68 66 61 70.1
#> 17.43 23.41 9.92 20.33 22.68 18.00 16.16 7.38 21.60 20.62 22.13 10.12 7.38
#> 180 166 150.2 168 145.3 23.2 18.1 30.1 91 8.1 128 66.1 79
#> 14.82 19.98 20.33 23.72 10.07 16.92 15.21 17.43 5.33 18.43 20.35 22.13 16.23
#> 168.1 10 29.5 81 136 5 61.1 136.1 57 140.1 58 167 99.1
#> 23.72 10.53 15.45 14.06 21.83 16.43 10.12 21.83 14.46 12.68 19.34 15.55 21.19
#> 171 52 167.1 149 180.1 128.1 164 10.1 58.1 26 86.1 122 165
#> 16.57 10.42 15.55 8.37 14.82 20.35 23.60 10.53 19.34 15.77 23.81 24.00 24.00
#> 48 103 64 138 27 27.1 141 72 163 34 120 173 19
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31 98 67 141.1 74 21 84 186 132 173.1 98.1 71 147
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 21.1 160 193 109 135 71.1 21.2 20 53 120.1 48.1 35 196
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 118 47 118.1 74.1 200 172 74.2 200.1 83 12 146 95 87
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80 112 156 31.1 3 98.2 122.1 94 95.1 47.1 148 84.1 75
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 191 84.2 182 87.1 160.1 109.1 27.2 144 31.2 67.1 62 95.2 147.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 146.1 83.1 191.1 72.1 121 147.2 118.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[43]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01481582 0.93163467 0.37177249
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.381032394 -0.007960621 0.044668450
#> grade_iii, Cure model
#> 0.571197382
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 60 13.15 1 38 1 0
#> 105 19.75 1 60 0 0
#> 37 12.52 1 57 1 0
#> 129 23.41 1 53 1 0
#> 77 7.27 1 67 0 1
#> 57 14.46 1 45 0 1
#> 91 5.33 1 61 0 1
#> 85 16.44 1 36 0 0
#> 149 8.37 1 33 1 0
#> 81 14.06 1 34 0 0
#> 58 19.34 1 39 0 0
#> 50 10.02 1 NA 1 0
#> 128 20.35 1 35 0 1
#> 86 23.81 1 58 0 1
#> 179 18.63 1 42 0 0
#> 105.1 19.75 1 60 0 0
#> 60.1 13.15 1 38 1 0
#> 140 12.68 1 59 1 0
#> 86.1 23.81 1 58 0 1
#> 179.1 18.63 1 42 0 0
#> 43 12.10 1 61 0 1
#> 39 15.59 1 37 0 1
#> 194 22.40 1 38 0 1
#> 88 18.37 1 47 0 0
#> 89 11.44 1 NA 0 0
#> 42 12.43 1 49 0 1
#> 29 15.45 1 68 1 0
#> 150 20.33 1 48 0 0
#> 26 15.77 1 49 0 1
#> 110 17.56 1 65 0 1
#> 128.1 20.35 1 35 0 1
#> 6 15.64 1 39 0 0
#> 18 15.21 1 49 1 0
#> 61 10.12 1 36 0 1
#> 39.1 15.59 1 37 0 1
#> 99 21.19 1 38 0 1
#> 190 20.81 1 42 1 0
#> 61.1 10.12 1 36 0 1
#> 130 16.47 1 53 0 1
#> 85.1 16.44 1 36 0 0
#> 79 16.23 1 54 1 0
#> 101 9.97 1 10 0 1
#> 6.1 15.64 1 39 0 0
#> 68 20.62 1 44 0 0
#> 133 14.65 1 57 0 0
#> 15 22.68 1 48 0 0
#> 85.2 16.44 1 36 0 0
#> 187 9.92 1 39 1 0
#> 51 18.23 1 83 0 1
#> 134 17.81 1 47 1 0
#> 199 19.81 1 NA 0 1
#> 57.1 14.46 1 45 0 1
#> 14 12.89 1 21 0 0
#> 149.1 8.37 1 33 1 0
#> 99.1 21.19 1 38 0 1
#> 24 23.89 1 38 0 0
#> 8 18.43 1 32 0 0
#> 37.1 12.52 1 57 1 0
#> 128.2 20.35 1 35 0 1
#> 125 15.65 1 67 1 0
#> 57.2 14.46 1 45 0 1
#> 70 7.38 1 30 1 0
#> 184 17.77 1 38 0 0
#> 106 16.67 1 49 1 0
#> 170 19.54 1 43 0 1
#> 10 10.53 1 34 0 0
#> 79.1 16.23 1 54 1 0
#> 51.1 18.23 1 83 0 1
#> 123 13.00 1 44 1 0
#> 37.2 12.52 1 57 1 0
#> 37.3 12.52 1 57 1 0
#> 91.1 5.33 1 61 0 1
#> 77.1 7.27 1 67 0 1
#> 25 6.32 1 34 1 0
#> 171 16.57 1 41 0 1
#> 96 14.54 1 33 0 1
#> 124 9.73 1 NA 1 0
#> 57.3 14.46 1 45 0 1
#> 175 21.91 1 43 0 0
#> 166 19.98 1 48 0 0
#> 180 14.82 1 37 0 0
#> 76 19.22 1 54 0 1
#> 187.1 9.92 1 39 1 0
#> 195 11.76 1 NA 1 0
#> 130.1 16.47 1 53 0 1
#> 55 19.34 1 69 0 1
#> 153 21.33 1 55 1 0
#> 159 10.55 1 50 0 1
#> 117 17.46 1 26 0 1
#> 24.1 23.89 1 38 0 0
#> 86.2 23.81 1 58 0 1
#> 50.1 10.02 1 NA 1 0
#> 145 10.07 1 65 1 0
#> 133.1 14.65 1 57 0 0
#> 5 16.43 1 51 0 1
#> 42.1 12.43 1 49 0 1
#> 164 23.60 1 76 0 1
#> 85.3 16.44 1 36 0 0
#> 58.1 19.34 1 39 0 0
#> 41 18.02 1 40 1 0
#> 106.1 16.67 1 49 1 0
#> 157 15.10 1 47 0 0
#> 184.1 17.77 1 38 0 0
#> 149.2 8.37 1 33 1 0
#> 179.2 18.63 1 42 0 0
#> 24.2 23.89 1 38 0 0
#> 96.1 14.54 1 33 0 1
#> 107 11.18 1 54 1 0
#> 158 20.14 1 74 1 0
#> 10.1 10.53 1 34 0 0
#> 55.1 19.34 1 69 0 1
#> 56 12.21 1 60 0 0
#> 2 24.00 0 9 0 0
#> 174 24.00 0 49 1 0
#> 147 24.00 0 76 1 0
#> 112 24.00 0 61 0 0
#> 152 24.00 0 36 0 1
#> 28 24.00 0 67 1 0
#> 80 24.00 0 41 0 0
#> 174.1 24.00 0 49 1 0
#> 34 24.00 0 36 0 0
#> 126 24.00 0 48 0 0
#> 1 24.00 0 23 1 0
#> 67 24.00 0 25 0 0
#> 71 24.00 0 51 0 0
#> 152.1 24.00 0 36 0 1
#> 174.2 24.00 0 49 1 0
#> 119 24.00 0 17 0 0
#> 103 24.00 0 56 1 0
#> 191 24.00 0 60 0 1
#> 31 24.00 0 36 0 1
#> 112.1 24.00 0 61 0 0
#> 67.1 24.00 0 25 0 0
#> 146 24.00 0 63 1 0
#> 116 24.00 0 58 0 1
#> 102 24.00 0 49 0 0
#> 161 24.00 0 45 0 0
#> 75 24.00 0 21 1 0
#> 11 24.00 0 42 0 1
#> 75.1 24.00 0 21 1 0
#> 20 24.00 0 46 1 0
#> 54 24.00 0 53 1 0
#> 200 24.00 0 64 0 0
#> 73 24.00 0 NA 0 1
#> 17 24.00 0 38 0 1
#> 147.1 24.00 0 76 1 0
#> 54.1 24.00 0 53 1 0
#> 198 24.00 0 66 0 1
#> 151 24.00 0 42 0 0
#> 109 24.00 0 48 0 0
#> 95 24.00 0 68 0 1
#> 1.1 24.00 0 23 1 0
#> 131 24.00 0 66 0 0
#> 173 24.00 0 19 0 1
#> 35 24.00 0 51 0 0
#> 28.1 24.00 0 67 1 0
#> 112.2 24.00 0 61 0 0
#> 198.1 24.00 0 66 0 1
#> 94 24.00 0 51 0 1
#> 143 24.00 0 51 0 0
#> 33 24.00 0 53 0 0
#> 161.1 24.00 0 45 0 0
#> 104 24.00 0 50 1 0
#> 198.2 24.00 0 66 0 1
#> 74 24.00 0 43 0 1
#> 54.2 24.00 0 53 1 0
#> 21 24.00 0 47 0 0
#> 95.1 24.00 0 68 0 1
#> 178 24.00 0 52 1 0
#> 20.1 24.00 0 46 1 0
#> 200.1 24.00 0 64 0 0
#> 135 24.00 0 58 1 0
#> 182 24.00 0 35 0 0
#> 82 24.00 0 34 0 0
#> 163 24.00 0 66 0 0
#> 151.1 24.00 0 42 0 0
#> 116.1 24.00 0 58 0 1
#> 165 24.00 0 47 0 0
#> 135.1 24.00 0 58 1 0
#> 143.1 24.00 0 51 0 0
#> 20.2 24.00 0 46 1 0
#> 53 24.00 0 32 0 1
#> 53.1 24.00 0 32 0 1
#> 185 24.00 0 44 1 0
#> 198.3 24.00 0 66 0 1
#> 156 24.00 0 50 1 0
#> 9 24.00 0 31 1 0
#> 115 24.00 0 NA 1 0
#> 109.1 24.00 0 48 0 0
#> 33.1 24.00 0 53 0 0
#> 173.1 24.00 0 19 0 1
#> 21.1 24.00 0 47 0 0
#> 54.3 24.00 0 53 1 0
#> 95.2 24.00 0 68 0 1
#> 84 24.00 0 39 0 1
#> 186 24.00 0 45 1 0
#> 191.1 24.00 0 60 0 1
#> 152.2 24.00 0 36 0 1
#> 121 24.00 0 57 1 0
#> 161.2 24.00 0 45 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.381 NA NA NA
#> 2 age, Cure model -0.00796 NA NA NA
#> 3 grade_ii, Cure model 0.0447 NA NA NA
#> 4 grade_iii, Cure model 0.571 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0148 NA NA NA
#> 2 grade_ii, Survival model 0.932 NA NA NA
#> 3 grade_iii, Survival model 0.372 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.381032 -0.007961 0.044668 0.571197
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.1
#> Residual Deviance: 260.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.381032394 -0.007960621 0.044668450 0.571197382
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01481582 0.93163467 0.37177249
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.630760573 0.115874879 0.688193991 0.024065316 0.942571718 0.573694766
#> [7] 0.976979829 0.348097582 0.897082044 0.619017331 0.137990049 0.077361050
#> [13] 0.008062588 0.177212027 0.115874879 0.630760573 0.676670042 0.008062588
#> [19] 0.177212027 0.767432243 0.462806446 0.034821302 0.212072569 0.732880232
#> [25] 0.484450123 0.095454259 0.420052563 0.279012700 0.077361050 0.441325391
#> [31] 0.495413712 0.826189964 0.462806446 0.052944558 0.064930422 0.826189964
#> [37] 0.328216420 0.348097582 0.399219471 0.861824054 0.441325391 0.071015438
#> [43] 0.528477606 0.029191052 0.348097582 0.873720092 0.221396066 0.250184413
#> [49] 0.573694766 0.665134470 0.897082044 0.052944558 0.001392778 0.202950268
#> [55] 0.688193991 0.077361050 0.430681195 0.573694766 0.931159559 0.259710729
#> [61] 0.298978973 0.130407639 0.802594225 0.399219471 0.221396066 0.653652148
#> [67] 0.688193991 0.688193991 0.976979829 0.942571718 0.965513274 0.318326771
#> [73] 0.551034856 0.573694766 0.040616393 0.108898678 0.517349848 0.168779575
#> [79] 0.873720092 0.328216420 0.137990049 0.046830054 0.790846068 0.288993518
#> [85] 0.001392778 0.008062588 0.849886728 0.528477606 0.388584402 0.732880232
#> [91] 0.018766877 0.348097582 0.137990049 0.240560948 0.298978973 0.506322191
#> [97] 0.259710729 0.897082044 0.177212027 0.001392778 0.551034856 0.779151522
#> [103] 0.102142805 0.802594225 0.137990049 0.755786338 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 60 105 37 129 77 57 91 85 149 81 58 128 86
#> 13.15 19.75 12.52 23.41 7.27 14.46 5.33 16.44 8.37 14.06 19.34 20.35 23.81
#> 179 105.1 60.1 140 86.1 179.1 43 39 194 88 42 29 150
#> 18.63 19.75 13.15 12.68 23.81 18.63 12.10 15.59 22.40 18.37 12.43 15.45 20.33
#> 26 110 128.1 6 18 61 39.1 99 190 61.1 130 85.1 79
#> 15.77 17.56 20.35 15.64 15.21 10.12 15.59 21.19 20.81 10.12 16.47 16.44 16.23
#> 101 6.1 68 133 15 85.2 187 51 134 57.1 14 149.1 99.1
#> 9.97 15.64 20.62 14.65 22.68 16.44 9.92 18.23 17.81 14.46 12.89 8.37 21.19
#> 24 8 37.1 128.2 125 57.2 70 184 106 170 10 79.1 51.1
#> 23.89 18.43 12.52 20.35 15.65 14.46 7.38 17.77 16.67 19.54 10.53 16.23 18.23
#> 123 37.2 37.3 91.1 77.1 25 171 96 57.3 175 166 180 76
#> 13.00 12.52 12.52 5.33 7.27 6.32 16.57 14.54 14.46 21.91 19.98 14.82 19.22
#> 187.1 130.1 55 153 159 117 24.1 86.2 145 133.1 5 42.1 164
#> 9.92 16.47 19.34 21.33 10.55 17.46 23.89 23.81 10.07 14.65 16.43 12.43 23.60
#> 85.3 58.1 41 106.1 157 184.1 149.2 179.2 24.2 96.1 107 158 10.1
#> 16.44 19.34 18.02 16.67 15.10 17.77 8.37 18.63 23.89 14.54 11.18 20.14 10.53
#> 55.1 56 2 174 147 112 152 28 80 174.1 34 126 1
#> 19.34 12.21 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67 71 152.1 174.2 119 103 191 31 112.1 67.1 146 116 102
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 161 75 11 75.1 20 54 200 17 147.1 54.1 198 151 109
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95 1.1 131 173 35 28.1 112.2 198.1 94 143 33 161.1 104
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 198.2 74 54.2 21 95.1 178 20.1 200.1 135 182 82 163 151.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116.1 165 135.1 143.1 20.2 53 53.1 185 198.3 156 9 109.1 33.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 173.1 21.1 54.3 95.2 84 186 191.1 152.2 121 161.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[44]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.003847724 1.104402134 0.604192277
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.43602189 0.02518405 0.02665437
#> grade_iii, Cure model
#> 1.54428548
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 194 22.40 1 38 0 1
#> 85 16.44 1 36 0 0
#> 158 20.14 1 74 1 0
#> 60 13.15 1 38 1 0
#> 51 18.23 1 83 0 1
#> 183 9.24 1 67 1 0
#> 69 23.23 1 25 0 1
#> 59 10.16 1 NA 1 0
#> 4 17.64 1 NA 0 1
#> 171 16.57 1 41 0 1
#> 36 21.19 1 48 0 1
#> 166 19.98 1 48 0 0
#> 177 12.53 1 75 0 0
#> 59.1 10.16 1 NA 1 0
#> 139 21.49 1 63 1 0
#> 85.1 16.44 1 36 0 0
#> 150 20.33 1 48 0 0
#> 26 15.77 1 49 0 1
#> 55 19.34 1 69 0 1
#> 106 16.67 1 49 1 0
#> 43 12.10 1 61 0 1
#> 133 14.65 1 57 0 0
#> 26.1 15.77 1 49 0 1
#> 97 19.14 1 65 0 1
#> 90 20.94 1 50 0 1
#> 168 23.72 1 70 0 0
#> 128 20.35 1 35 0 1
#> 188 16.16 1 46 0 1
#> 29 15.45 1 68 1 0
#> 184 17.77 1 38 0 0
#> 194.1 22.40 1 38 0 1
#> 52 10.42 1 52 0 1
#> 194.2 22.40 1 38 0 1
#> 15 22.68 1 48 0 0
#> 168.1 23.72 1 70 0 0
#> 149 8.37 1 33 1 0
#> 123 13.00 1 44 1 0
#> 25 6.32 1 34 1 0
#> 195 11.76 1 NA 1 0
#> 108 18.29 1 39 0 1
#> 113 22.86 1 34 0 0
#> 184.1 17.77 1 38 0 0
#> 133.1 14.65 1 57 0 0
#> 111 17.45 1 47 0 1
#> 157 15.10 1 47 0 0
#> 15.1 22.68 1 48 0 0
#> 97.1 19.14 1 65 0 1
#> 59.2 10.16 1 NA 1 0
#> 57 14.46 1 45 0 1
#> 63 22.77 1 31 1 0
#> 140 12.68 1 59 1 0
#> 8 18.43 1 32 0 0
#> 40 18.00 1 28 1 0
#> 167 15.55 1 56 1 0
#> 188.1 16.16 1 46 0 1
#> 110 17.56 1 65 0 1
#> 45 17.42 1 54 0 1
#> 57.1 14.46 1 45 0 1
#> 111.1 17.45 1 47 0 1
#> 51.1 18.23 1 83 0 1
#> 96 14.54 1 33 0 1
#> 192 16.44 1 31 1 0
#> 187 9.92 1 39 1 0
#> 111.2 17.45 1 47 0 1
#> 66 22.13 1 53 0 0
#> 10 10.53 1 34 0 0
#> 39 15.59 1 37 0 1
#> 111.3 17.45 1 47 0 1
#> 153 21.33 1 55 1 0
#> 56 12.21 1 60 0 0
#> 13 14.34 1 54 0 1
#> 41 18.02 1 40 1 0
#> 78 23.88 1 43 0 0
#> 58 19.34 1 39 0 0
#> 127 3.53 1 62 0 1
#> 96.1 14.54 1 33 0 1
#> 60.1 13.15 1 38 1 0
#> 78.1 23.88 1 43 0 0
#> 158.1 20.14 1 74 1 0
#> 50 10.02 1 NA 1 0
#> 140.1 12.68 1 59 1 0
#> 170 19.54 1 43 0 1
#> 157.1 15.10 1 47 0 0
#> 51.2 18.23 1 83 0 1
#> 140.2 12.68 1 59 1 0
#> 96.2 14.54 1 33 0 1
#> 101 9.97 1 10 0 1
#> 171.1 16.57 1 41 0 1
#> 140.3 12.68 1 59 1 0
#> 164 23.60 1 76 0 1
#> 96.3 14.54 1 33 0 1
#> 24 23.89 1 38 0 0
#> 25.1 6.32 1 34 1 0
#> 88 18.37 1 47 0 0
#> 41.1 18.02 1 40 1 0
#> 199 19.81 1 NA 0 1
#> 5 16.43 1 51 0 1
#> 37 12.52 1 57 1 0
#> 184.2 17.77 1 38 0 0
#> 139.1 21.49 1 63 1 0
#> 189 10.51 1 NA 1 0
#> 187.1 9.92 1 39 1 0
#> 145 10.07 1 65 1 0
#> 199.1 19.81 1 NA 0 1
#> 195.1 11.76 1 NA 1 0
#> 92 22.92 1 47 0 1
#> 194.3 22.40 1 38 0 1
#> 145.1 10.07 1 65 1 0
#> 55.1 19.34 1 69 0 1
#> 90.1 20.94 1 50 0 1
#> 51.3 18.23 1 83 0 1
#> 93 10.33 1 52 0 1
#> 141 24.00 0 44 1 0
#> 27 24.00 0 63 1 0
#> 116 24.00 0 58 0 1
#> 9 24.00 0 31 1 0
#> 7 24.00 0 37 1 0
#> 7.1 24.00 0 37 1 0
#> 2 24.00 0 9 0 0
#> 28 24.00 0 67 1 0
#> 193 24.00 0 45 0 1
#> 73 24.00 0 NA 0 1
#> 80 24.00 0 41 0 0
#> 44 24.00 0 56 0 0
#> 87 24.00 0 27 0 0
#> 22 24.00 0 52 1 0
#> 83 24.00 0 6 0 0
#> 98 24.00 0 34 1 0
#> 1 24.00 0 23 1 0
#> 72 24.00 0 40 0 1
#> 115 24.00 0 NA 1 0
#> 115.1 24.00 0 NA 1 0
#> 173 24.00 0 19 0 1
#> 72.1 24.00 0 40 0 1
#> 196 24.00 0 19 0 0
#> 80.1 24.00 0 41 0 0
#> 112 24.00 0 61 0 0
#> 131 24.00 0 66 0 0
#> 98.1 24.00 0 34 1 0
#> 21 24.00 0 47 0 0
#> 172 24.00 0 41 0 0
#> 122 24.00 0 66 0 0
#> 138 24.00 0 44 1 0
#> 1.1 24.00 0 23 1 0
#> 87.1 24.00 0 27 0 0
#> 73.1 24.00 0 NA 0 1
#> 121 24.00 0 57 1 0
#> 116.1 24.00 0 58 0 1
#> 156 24.00 0 50 1 0
#> 146 24.00 0 63 1 0
#> 12 24.00 0 63 0 0
#> 38 24.00 0 31 1 0
#> 121.1 24.00 0 57 1 0
#> 3 24.00 0 31 1 0
#> 118 24.00 0 44 1 0
#> 185 24.00 0 44 1 0
#> 112.1 24.00 0 61 0 0
#> 34 24.00 0 36 0 0
#> 2.1 24.00 0 9 0 0
#> 87.2 24.00 0 27 0 0
#> 144 24.00 0 28 0 1
#> 163 24.00 0 66 0 0
#> 137 24.00 0 45 1 0
#> 28.1 24.00 0 67 1 0
#> 65 24.00 0 57 1 0
#> 165 24.00 0 47 0 0
#> 83.1 24.00 0 6 0 0
#> 185.1 24.00 0 44 1 0
#> 131.1 24.00 0 66 0 0
#> 138.1 24.00 0 44 1 0
#> 82 24.00 0 34 0 0
#> 182 24.00 0 35 0 0
#> 160 24.00 0 31 1 0
#> 126 24.00 0 48 0 0
#> 196.1 24.00 0 19 0 0
#> 46 24.00 0 71 0 0
#> 19 24.00 0 57 0 1
#> 118.1 24.00 0 44 1 0
#> 132 24.00 0 55 0 0
#> 94 24.00 0 51 0 1
#> 112.2 24.00 0 61 0 0
#> 67 24.00 0 25 0 0
#> 131.2 24.00 0 66 0 0
#> 144.1 24.00 0 28 0 1
#> 48 24.00 0 31 1 0
#> 163.1 24.00 0 66 0 0
#> 151 24.00 0 42 0 0
#> 28.2 24.00 0 67 1 0
#> 121.2 24.00 0 57 1 0
#> 54 24.00 0 53 1 0
#> 160.1 24.00 0 31 1 0
#> 178 24.00 0 52 1 0
#> 84 24.00 0 39 0 1
#> 152 24.00 0 36 0 1
#> 98.2 24.00 0 34 1 0
#> 80.2 24.00 0 41 0 0
#> 7.2 24.00 0 37 1 0
#> 116.2 24.00 0 58 0 1
#> 126.1 24.00 0 48 0 0
#> 185.2 24.00 0 44 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.44 NA NA NA
#> 2 age, Cure model 0.0252 NA NA NA
#> 3 grade_ii, Cure model 0.0267 NA NA NA
#> 4 grade_iii, Cure model 1.54 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00385 NA NA NA
#> 2 grade_ii, Survival model 1.10 NA NA NA
#> 3 grade_iii, Survival model 0.604 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.43602 0.02518 0.02665 1.54429
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 256.1
#> Residual Deviance: 229.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.43602189 0.02518405 0.02665437 1.54428548
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.003847724 1.104402134 0.604192277
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.23527604 0.67617898 0.39235478 0.84331748 0.51139317 0.96944489
#> [7] 0.13073109 0.65994820 0.33689484 0.41263396 0.89101198 0.30083564
#> [13] 0.67617898 0.38134897 0.72363183 0.43311859 0.65166698 0.91103993
#> [19] 0.77708478 0.72363183 0.46248101 0.34843211 0.06671023 0.37039649
#> [25] 0.70795341 0.75451536 0.57507677 0.23527604 0.92432066 0.23527604
#> [31] 0.20366120 0.06671023 0.97569464 0.85746934 0.98187874 0.50163018
#> [37] 0.16891883 0.57507677 0.77708478 0.60990733 0.76204700 0.20366120
#> [43] 0.46248101 0.82140852 0.18762990 0.86448475 0.48191602 0.56630793
#> [49] 0.74688295 0.70795341 0.60114412 0.64322495 0.82140852 0.60990733
#> [55] 0.51139317 0.79218010 0.67617898 0.95687813 0.60990733 0.28684514
#> [61] 0.91767735 0.73913714 0.60990733 0.32514795 0.90438083 0.83601382
#> [67] 0.54843676 0.03053279 0.43311859 0.99395811 0.79218010 0.84331748
#> [73] 0.03053279 0.39235478 0.86448475 0.42294456 0.76204700 0.51139317
#> [79] 0.86448475 0.79218010 0.95043848 0.65994820 0.86448475 0.10882526
#> [85] 0.79218010 0.00959611 0.98187874 0.49175676 0.54843676 0.69997563
#> [91] 0.89773182 0.57507677 0.30083564 0.95687813 0.93753654 0.15046031
#> [97] 0.23527604 0.93753654 0.43311859 0.34843211 0.51139317 0.93094028
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 194 85 158 60 51 183 69 171 36 166 177 139 85.1
#> 22.40 16.44 20.14 13.15 18.23 9.24 23.23 16.57 21.19 19.98 12.53 21.49 16.44
#> 150 26 55 106 43 133 26.1 97 90 168 128 188 29
#> 20.33 15.77 19.34 16.67 12.10 14.65 15.77 19.14 20.94 23.72 20.35 16.16 15.45
#> 184 194.1 52 194.2 15 168.1 149 123 25 108 113 184.1 133.1
#> 17.77 22.40 10.42 22.40 22.68 23.72 8.37 13.00 6.32 18.29 22.86 17.77 14.65
#> 111 157 15.1 97.1 57 63 140 8 40 167 188.1 110 45
#> 17.45 15.10 22.68 19.14 14.46 22.77 12.68 18.43 18.00 15.55 16.16 17.56 17.42
#> 57.1 111.1 51.1 96 192 187 111.2 66 10 39 111.3 153 56
#> 14.46 17.45 18.23 14.54 16.44 9.92 17.45 22.13 10.53 15.59 17.45 21.33 12.21
#> 13 41 78 58 127 96.1 60.1 78.1 158.1 140.1 170 157.1 51.2
#> 14.34 18.02 23.88 19.34 3.53 14.54 13.15 23.88 20.14 12.68 19.54 15.10 18.23
#> 140.2 96.2 101 171.1 140.3 164 96.3 24 25.1 88 41.1 5 37
#> 12.68 14.54 9.97 16.57 12.68 23.60 14.54 23.89 6.32 18.37 18.02 16.43 12.52
#> 184.2 139.1 187.1 145 92 194.3 145.1 55.1 90.1 51.3 93 141 27
#> 17.77 21.49 9.92 10.07 22.92 22.40 10.07 19.34 20.94 18.23 10.33 24.00 24.00
#> 116 9 7 7.1 2 28 193 80 44 87 22 83 98
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1 72 173 72.1 196 80.1 112 131 98.1 21 172 122 138
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1.1 87.1 121 116.1 156 146 12 38 121.1 3 118 185 112.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34 2.1 87.2 144 163 137 28.1 65 165 83.1 185.1 131.1 138.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 82 182 160 126 196.1 46 19 118.1 132 94 112.2 67 131.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 144.1 48 163.1 151 28.2 121.2 54 160.1 178 84 152 98.2 80.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 7.2 116.2 126.1 185.2
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[45]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01254847 0.35051736 0.47725085
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.91291993 0.01651989 0.17770238
#> grade_iii, Cure model
#> 0.97825877
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 90 20.94 1 50 0 1
#> 169 22.41 1 46 0 0
#> 139 21.49 1 63 1 0
#> 168 23.72 1 70 0 0
#> 108 18.29 1 39 0 1
#> 192 16.44 1 31 1 0
#> 170 19.54 1 43 0 1
#> 85 16.44 1 36 0 0
#> 93 10.33 1 52 0 1
#> 136 21.83 1 43 0 1
#> 105 19.75 1 60 0 0
#> 10 10.53 1 34 0 0
#> 158 20.14 1 74 1 0
#> 89 11.44 1 NA 0 0
#> 134 17.81 1 47 1 0
#> 77 7.27 1 67 0 1
#> 129 23.41 1 53 1 0
#> 24 23.89 1 38 0 0
#> 49 12.19 1 48 1 0
#> 6 15.64 1 39 0 0
#> 37 12.52 1 57 1 0
#> 4 17.64 1 NA 0 1
#> 10.1 10.53 1 34 0 0
#> 179 18.63 1 42 0 0
#> 136.1 21.83 1 43 0 1
#> 153 21.33 1 55 1 0
#> 40 18.00 1 28 1 0
#> 58 19.34 1 39 0 0
#> 177 12.53 1 75 0 0
#> 92 22.92 1 47 0 1
#> 164 23.60 1 76 0 1
#> 184 17.77 1 38 0 0
#> 79 16.23 1 54 1 0
#> 49.1 12.19 1 48 1 0
#> 187 9.92 1 39 1 0
#> 24.1 23.89 1 38 0 0
#> 108.1 18.29 1 39 0 1
#> 108.2 18.29 1 39 0 1
#> 153.1 21.33 1 55 1 0
#> 114 13.68 1 NA 0 0
#> 195 11.76 1 NA 1 0
#> 5 16.43 1 51 0 1
#> 155 13.08 1 26 0 0
#> 6.1 15.64 1 39 0 0
#> 190 20.81 1 42 1 0
#> 123 13.00 1 44 1 0
#> 45 17.42 1 54 0 1
#> 10.2 10.53 1 34 0 0
#> 133 14.65 1 57 0 0
#> 13 14.34 1 54 0 1
#> 179.1 18.63 1 42 0 0
#> 56 12.21 1 60 0 0
#> 171 16.57 1 41 0 1
#> 16 8.71 1 71 0 1
#> 43 12.10 1 61 0 1
#> 60 13.15 1 38 1 0
#> 189 10.51 1 NA 1 0
#> 129.1 23.41 1 53 1 0
#> 57 14.46 1 45 0 1
#> 111 17.45 1 47 0 1
#> 57.1 14.46 1 45 0 1
#> 127 3.53 1 62 0 1
#> 16.1 8.71 1 71 0 1
#> 43.1 12.10 1 61 0 1
#> 41 18.02 1 40 1 0
#> 60.1 13.15 1 38 1 0
#> 101 9.97 1 10 0 1
#> 99 21.19 1 38 0 1
#> 79.1 16.23 1 54 1 0
#> 188 16.16 1 46 0 1
#> 127.1 3.53 1 62 0 1
#> 30 17.43 1 78 0 0
#> 130 16.47 1 53 0 1
#> 66 22.13 1 53 0 0
#> 106 16.67 1 49 1 0
#> 184.1 17.77 1 38 0 0
#> 123.1 13.00 1 44 1 0
#> 149 8.37 1 33 1 0
#> 168.1 23.72 1 70 0 0
#> 129.2 23.41 1 53 1 0
#> 40.1 18.00 1 28 1 0
#> 4.1 17.64 1 NA 0 1
#> 136.2 21.83 1 43 0 1
#> 76 19.22 1 54 0 1
#> 187.1 9.92 1 39 1 0
#> 153.2 21.33 1 55 1 0
#> 97 19.14 1 65 0 1
#> 61 10.12 1 36 0 1
#> 63 22.77 1 31 1 0
#> 99.1 21.19 1 38 0 1
#> 61.1 10.12 1 36 0 1
#> 169.1 22.41 1 46 0 0
#> 13.1 14.34 1 54 0 1
#> 70 7.38 1 30 1 0
#> 85.1 16.44 1 36 0 0
#> 149.1 8.37 1 33 1 0
#> 100 16.07 1 60 0 0
#> 127.2 3.53 1 62 0 1
#> 26 15.77 1 49 0 1
#> 23 16.92 1 61 0 0
#> 136.3 21.83 1 43 0 1
#> 76.1 19.22 1 54 0 1
#> 168.2 23.72 1 70 0 0
#> 70.1 7.38 1 30 1 0
#> 101.1 9.97 1 10 0 1
#> 93.1 10.33 1 52 0 1
#> 23.1 16.92 1 61 0 0
#> 39 15.59 1 37 0 1
#> 10.3 10.53 1 34 0 0
#> 188.1 16.16 1 46 0 1
#> 177.1 12.53 1 75 0 0
#> 99.2 21.19 1 38 0 1
#> 21 24.00 0 47 0 0
#> 19 24.00 0 57 0 1
#> 102 24.00 0 49 0 0
#> 27 24.00 0 63 1 0
#> 193 24.00 0 45 0 1
#> 109 24.00 0 48 0 0
#> 71 24.00 0 51 0 0
#> 48 24.00 0 31 1 0
#> 44 24.00 0 56 0 0
#> 71.1 24.00 0 51 0 0
#> 121 24.00 0 57 1 0
#> 67 24.00 0 25 0 0
#> 148 24.00 0 61 1 0
#> 20 24.00 0 46 1 0
#> 17 24.00 0 38 0 1
#> 102.1 24.00 0 49 0 0
#> 28 24.00 0 67 1 0
#> 83 24.00 0 6 0 0
#> 135 24.00 0 58 1 0
#> 71.2 24.00 0 51 0 0
#> 193.1 24.00 0 45 0 1
#> 131 24.00 0 66 0 0
#> 185 24.00 0 44 1 0
#> 115 24.00 0 NA 1 0
#> 82 24.00 0 34 0 0
#> 28.1 24.00 0 67 1 0
#> 73 24.00 0 NA 0 1
#> 137 24.00 0 45 1 0
#> 54 24.00 0 53 1 0
#> 2 24.00 0 9 0 0
#> 118 24.00 0 44 1 0
#> 116 24.00 0 58 0 1
#> 138 24.00 0 44 1 0
#> 28.2 24.00 0 67 1 0
#> 11 24.00 0 42 0 1
#> 102.2 24.00 0 49 0 0
#> 95 24.00 0 68 0 1
#> 34 24.00 0 36 0 0
#> 196 24.00 0 19 0 0
#> 38 24.00 0 31 1 0
#> 2.1 24.00 0 9 0 0
#> 67.1 24.00 0 25 0 0
#> 19.1 24.00 0 57 0 1
#> 65 24.00 0 57 1 0
#> 98 24.00 0 34 1 0
#> 67.2 24.00 0 25 0 0
#> 87 24.00 0 27 0 0
#> 3 24.00 0 31 1 0
#> 84 24.00 0 39 0 1
#> 28.3 24.00 0 67 1 0
#> 64 24.00 0 43 0 0
#> 109.1 24.00 0 48 0 0
#> 178 24.00 0 52 1 0
#> 112 24.00 0 61 0 0
#> 152 24.00 0 36 0 1
#> 165 24.00 0 47 0 0
#> 82.1 24.00 0 34 0 0
#> 84.1 24.00 0 39 0 1
#> 33 24.00 0 53 0 0
#> 116.1 24.00 0 58 0 1
#> 75 24.00 0 21 1 0
#> 172 24.00 0 41 0 0
#> 185.1 24.00 0 44 1 0
#> 156 24.00 0 50 1 0
#> 182 24.00 0 35 0 0
#> 119 24.00 0 17 0 0
#> 174 24.00 0 49 1 0
#> 143 24.00 0 51 0 0
#> 144 24.00 0 28 0 1
#> 144.1 24.00 0 28 0 1
#> 1 24.00 0 23 1 0
#> 20.1 24.00 0 46 1 0
#> 120 24.00 0 68 0 1
#> 53 24.00 0 32 0 1
#> 152.1 24.00 0 36 0 1
#> 162 24.00 0 51 0 0
#> 64.1 24.00 0 43 0 0
#> 151 24.00 0 42 0 0
#> 137.1 24.00 0 45 1 0
#> 104 24.00 0 50 1 0
#> 33.1 24.00 0 53 0 0
#> 142 24.00 0 53 0 0
#> 34.1 24.00 0 36 0 0
#> 178.1 24.00 0 52 1 0
#> 176 24.00 0 43 0 1
#> 22 24.00 0 52 1 0
#> 176.1 24.00 0 43 0 1
#> 109.2 24.00 0 48 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.913 NA NA NA
#> 2 age, Cure model 0.0165 NA NA NA
#> 3 grade_ii, Cure model 0.178 NA NA NA
#> 4 grade_iii, Cure model 0.978 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0125 NA NA NA
#> 2 grade_ii, Survival model 0.351 NA NA NA
#> 3 grade_iii, Survival model 0.477 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.91292 0.01652 0.17770 0.97826
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.1
#> Residual Deviance: 253.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.91291993 0.01651989 0.17770238 0.97825877
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01254847 0.35051736 0.47725085
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.1495183930 0.0493151104 0.0967654969 0.0044966303 0.2432714114
#> [6] 0.4029628864 0.1822700677 0.4029628864 0.7853284897 0.0703565479
#> [11] 0.1738184867 0.7385831326 0.1655788797 0.2968331213 0.9518117393
#> [16] 0.0207150976 0.0008979413 0.6923003397 0.5055655937 0.6693325739
#> [21] 0.7385831326 0.2253562921 0.0703565479 0.1043843834 0.2788309666
#> [26] 0.1907454638 0.6467792929 0.0364881940 0.0150172256 0.3060352981
#> [31] 0.4432088926 0.6923003397 0.8565498358 0.0008979413 0.2432714114
#> [36] 0.2432714114 0.1043843834 0.4329401006 0.6136265892 0.5055655937
#> [41] 0.1575154769 0.6246956362 0.3436246636 0.7385831326 0.5376125205
#> [46] 0.5700622302 0.2253562921 0.6807652166 0.3828967359 0.8801792551
#> [51] 0.7153479886 0.5917967986 0.0207150976 0.5484771683 0.3245797568
#> [56] 0.5484771683 0.9638846932 0.8801792551 0.7153479886 0.2696804302
#> [61] 0.5917967986 0.8330046719 0.1269468620 0.4432088926 0.4637714278
#> [66] 0.9638846932 0.3340174821 0.3929078704 0.0627926372 0.3728951740
#> [71] 0.3060352981 0.6246956362 0.9040255902 0.0044966303 0.0207150976
#> [76] 0.2788309666 0.0703565479 0.1993691892 0.8565498358 0.1043843834
#> [81] 0.2165077243 0.8091756259 0.0428826788 0.1269468620 0.8091756259
#> [86] 0.0493151104 0.5700622302 0.9279107722 0.4029628864 0.9040255902
#> [91] 0.4844212092 0.9638846932 0.4949788810 0.3532808782 0.0703565479
#> [96] 0.1993691892 0.0044966303 0.9279107722 0.8330046719 0.7853284897
#> [101] 0.3532808782 0.5268589132 0.7385831326 0.4637714278 0.6467792929
#> [106] 0.1269468620 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [191] 0.0000000000 0.0000000000
#>
#> $Time
#> 90 169 139 168 108 192 170 85 93 136 105 10 158
#> 20.94 22.41 21.49 23.72 18.29 16.44 19.54 16.44 10.33 21.83 19.75 10.53 20.14
#> 134 77 129 24 49 6 37 10.1 179 136.1 153 40 58
#> 17.81 7.27 23.41 23.89 12.19 15.64 12.52 10.53 18.63 21.83 21.33 18.00 19.34
#> 177 92 164 184 79 49.1 187 24.1 108.1 108.2 153.1 5 155
#> 12.53 22.92 23.60 17.77 16.23 12.19 9.92 23.89 18.29 18.29 21.33 16.43 13.08
#> 6.1 190 123 45 10.2 133 13 179.1 56 171 16 43 60
#> 15.64 20.81 13.00 17.42 10.53 14.65 14.34 18.63 12.21 16.57 8.71 12.10 13.15
#> 129.1 57 111 57.1 127 16.1 43.1 41 60.1 101 99 79.1 188
#> 23.41 14.46 17.45 14.46 3.53 8.71 12.10 18.02 13.15 9.97 21.19 16.23 16.16
#> 127.1 30 130 66 106 184.1 123.1 149 168.1 129.2 40.1 136.2 76
#> 3.53 17.43 16.47 22.13 16.67 17.77 13.00 8.37 23.72 23.41 18.00 21.83 19.22
#> 187.1 153.2 97 61 63 99.1 61.1 169.1 13.1 70 85.1 149.1 100
#> 9.92 21.33 19.14 10.12 22.77 21.19 10.12 22.41 14.34 7.38 16.44 8.37 16.07
#> 127.2 26 23 136.3 76.1 168.2 70.1 101.1 93.1 23.1 39 10.3 188.1
#> 3.53 15.77 16.92 21.83 19.22 23.72 7.38 9.97 10.33 16.92 15.59 10.53 16.16
#> 177.1 99.2 21 19 102 27 193 109 71 48 44 71.1 121
#> 12.53 21.19 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67 148 20 17 102.1 28 83 135 71.2 193.1 131 185 82
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28.1 137 54 2 118 116 138 28.2 11 102.2 95 34 196
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 38 2.1 67.1 19.1 65 98 67.2 87 3 84 28.3 64 109.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178 112 152 165 82.1 84.1 33 116.1 75 172 185.1 156 182
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 119 174 143 144 144.1 1 20.1 120 53 152.1 162 64.1 151
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137.1 104 33.1 142 34.1 178.1 176 22 176.1 109.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[46]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.01562062 0.78846021 0.59276167
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.31462813 0.03314576 -0.59725414
#> grade_iii, Cure model
#> 0.49741593
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 128 20.35 1 35 0 1
#> 24 23.89 1 38 0 0
#> 41 18.02 1 40 1 0
#> 63 22.77 1 31 1 0
#> 170 19.54 1 43 0 1
#> 66 22.13 1 53 0 0
#> 43 12.10 1 61 0 1
#> 24.1 23.89 1 38 0 0
#> 88 18.37 1 47 0 0
#> 108 18.29 1 39 0 1
#> 61 10.12 1 36 0 1
#> 14 12.89 1 21 0 0
#> 68 20.62 1 44 0 0
#> 79 16.23 1 54 1 0
#> 150 20.33 1 48 0 0
#> 125 15.65 1 67 1 0
#> 29 15.45 1 68 1 0
#> 158 20.14 1 74 1 0
#> 58 19.34 1 39 0 0
#> 30 17.43 1 78 0 0
#> 124 9.73 1 NA 1 0
#> 195 11.76 1 NA 1 0
#> 177 12.53 1 75 0 0
#> 52 10.42 1 52 0 1
#> 187 9.92 1 39 1 0
#> 24.2 23.89 1 38 0 0
#> 136 21.83 1 43 0 1
#> 133 14.65 1 57 0 0
#> 177.1 12.53 1 75 0 0
#> 177.2 12.53 1 75 0 0
#> 51 18.23 1 83 0 1
#> 97 19.14 1 65 0 1
#> 25 6.32 1 34 1 0
#> 167 15.55 1 56 1 0
#> 107 11.18 1 54 1 0
#> 159 10.55 1 50 0 1
#> 36 21.19 1 48 0 1
#> 63.1 22.77 1 31 1 0
#> 164 23.60 1 76 0 1
#> 106 16.67 1 49 1 0
#> 69 23.23 1 25 0 1
#> 190 20.81 1 42 1 0
#> 15 22.68 1 48 0 0
#> 8 18.43 1 32 0 0
#> 81 14.06 1 34 0 0
#> 125.1 15.65 1 67 1 0
#> 197 21.60 1 69 1 0
#> 108.1 18.29 1 39 0 1
#> 194 22.40 1 38 0 1
#> 177.3 12.53 1 75 0 0
#> 113 22.86 1 34 0 0
#> 187.1 9.92 1 39 1 0
#> 171 16.57 1 41 0 1
#> 88.1 18.37 1 47 0 0
#> 127 3.53 1 62 0 1
#> 130 16.47 1 53 0 1
#> 76 19.22 1 54 0 1
#> 113.1 22.86 1 34 0 0
#> 125.2 15.65 1 67 1 0
#> 99 21.19 1 38 0 1
#> 69.1 23.23 1 25 0 1
#> 169 22.41 1 46 0 0
#> 57 14.46 1 45 0 1
#> 14.1 12.89 1 21 0 0
#> 77 7.27 1 67 0 1
#> 166 19.98 1 48 0 0
#> 91 5.33 1 61 0 1
#> 187.2 9.92 1 39 1 0
#> 8.1 18.43 1 32 0 0
#> 93 10.33 1 52 0 1
#> 99.1 21.19 1 38 0 1
#> 59 10.16 1 NA 1 0
#> 127.1 3.53 1 62 0 1
#> 99.2 21.19 1 38 0 1
#> 134 17.81 1 47 1 0
#> 123 13.00 1 44 1 0
#> 187.3 9.92 1 39 1 0
#> 52.1 10.42 1 52 0 1
#> 111 17.45 1 47 0 1
#> 149 8.37 1 33 1 0
#> 26 15.77 1 49 0 1
#> 199 19.81 1 NA 0 1
#> 91.1 5.33 1 61 0 1
#> 166.1 19.98 1 48 0 0
#> 153 21.33 1 55 1 0
#> 114 13.68 1 NA 0 0
#> 100 16.07 1 60 0 0
#> 188 16.16 1 46 0 1
#> 168 23.72 1 70 0 0
#> 105 19.75 1 60 0 0
#> 111.1 17.45 1 47 0 1
#> 51.1 18.23 1 83 0 1
#> 97.1 19.14 1 65 0 1
#> 13 14.34 1 54 0 1
#> 76.1 19.22 1 54 0 1
#> 181 16.46 1 45 0 1
#> 66.1 22.13 1 53 0 0
#> 16 8.71 1 71 0 1
#> 26.1 15.77 1 49 0 1
#> 93.1 10.33 1 52 0 1
#> 145 10.07 1 65 1 0
#> 49 12.19 1 48 1 0
#> 77.1 7.27 1 67 0 1
#> 81.1 14.06 1 34 0 0
#> 183 9.24 1 67 1 0
#> 188.1 16.16 1 46 0 1
#> 145.1 10.07 1 65 1 0
#> 43.1 12.10 1 61 0 1
#> 13.1 14.34 1 54 0 1
#> 93.2 10.33 1 52 0 1
#> 183.1 9.24 1 67 1 0
#> 180 14.82 1 37 0 0
#> 121 24.00 0 57 1 0
#> 165 24.00 0 47 0 0
#> 9 24.00 0 31 1 0
#> 104 24.00 0 50 1 0
#> 144 24.00 0 28 0 1
#> 9.1 24.00 0 31 1 0
#> 103 24.00 0 56 1 0
#> 152 24.00 0 36 0 1
#> 147 24.00 0 76 1 0
#> 151 24.00 0 42 0 0
#> 72 24.00 0 40 0 1
#> 103.1 24.00 0 56 1 0
#> 147.1 24.00 0 76 1 0
#> 156 24.00 0 50 1 0
#> 198 24.00 0 66 0 1
#> 22 24.00 0 52 1 0
#> 82 24.00 0 34 0 0
#> 152.1 24.00 0 36 0 1
#> 95 24.00 0 68 0 1
#> 118 24.00 0 44 1 0
#> 1 24.00 0 23 1 0
#> 2 24.00 0 9 0 0
#> 126 24.00 0 48 0 0
#> 122 24.00 0 66 0 0
#> 135 24.00 0 58 1 0
#> 185 24.00 0 44 1 0
#> 182 24.00 0 35 0 0
#> 151.1 24.00 0 42 0 0
#> 174 24.00 0 49 1 0
#> 115 24.00 0 NA 1 0
#> 54 24.00 0 53 1 0
#> 71 24.00 0 51 0 0
#> 47 24.00 0 38 0 1
#> 53 24.00 0 32 0 1
#> 22.1 24.00 0 52 1 0
#> 137 24.00 0 45 1 0
#> 84 24.00 0 39 0 1
#> 165.1 24.00 0 47 0 0
#> 141 24.00 0 44 1 0
#> 1.1 24.00 0 23 1 0
#> 174.1 24.00 0 49 1 0
#> 46 24.00 0 71 0 0
#> 35 24.00 0 51 0 0
#> 172 24.00 0 41 0 0
#> 118.1 24.00 0 44 1 0
#> 121.1 24.00 0 57 1 0
#> 196 24.00 0 19 0 0
#> 191 24.00 0 60 0 1
#> 95.1 24.00 0 68 0 1
#> 176 24.00 0 43 0 1
#> 98 24.00 0 34 1 0
#> 173 24.00 0 19 0 1
#> 46.1 24.00 0 71 0 0
#> 118.2 24.00 0 44 1 0
#> 186 24.00 0 45 1 0
#> 87 24.00 0 27 0 0
#> 152.2 24.00 0 36 0 1
#> 109 24.00 0 48 0 0
#> 160 24.00 0 31 1 0
#> 122.1 24.00 0 66 0 0
#> 94 24.00 0 51 0 1
#> 72.1 24.00 0 40 0 1
#> 186.1 24.00 0 45 1 0
#> 72.2 24.00 0 40 0 1
#> 98.1 24.00 0 34 1 0
#> 109.1 24.00 0 48 0 0
#> 173.1 24.00 0 19 0 1
#> 160.1 24.00 0 31 1 0
#> 82.1 24.00 0 34 0 0
#> 173.2 24.00 0 19 0 1
#> 2.1 24.00 0 9 0 0
#> 87.1 24.00 0 27 0 0
#> 151.2 24.00 0 42 0 0
#> 75 24.00 0 21 1 0
#> 172.1 24.00 0 41 0 0
#> 34 24.00 0 36 0 0
#> 147.2 24.00 0 76 1 0
#> 2.2 24.00 0 9 0 0
#> 54.1 24.00 0 53 1 0
#> 178 24.00 0 52 1 0
#> 9.2 24.00 0 31 1 0
#> 75.1 24.00 0 21 1 0
#> 138 24.00 0 44 1 0
#> 152.3 24.00 0 36 0 1
#> 120 24.00 0 68 0 1
#> 163 24.00 0 66 0 0
#> 7 24.00 0 37 1 0
#> 191.1 24.00 0 60 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.31 NA NA NA
#> 2 age, Cure model 0.0331 NA NA NA
#> 3 grade_ii, Cure model -0.597 NA NA NA
#> 4 grade_iii, Cure model 0.497 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0156 NA NA NA
#> 2 grade_ii, Survival model 0.788 NA NA NA
#> 3 grade_iii, Survival model 0.593 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.31463 0.03315 -0.59725 0.49742
#>
#> Degrees of Freedom: 193 Total (i.e. Null); 190 Residual
#> Null Deviance: 266.9
#> Residual Deviance: 247.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.31462813 0.03314576 -0.59725414 0.49741593
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.01562062 0.78846021 0.59276167
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.6539609 0.1836751 0.7848048 0.4650823 0.6995593 0.5417931 0.9243567
#> [8] 0.1836751 0.7509216 0.7627848 0.9520481 0.9009493 0.6455593 0.8281548
#> [15] 0.6621392 0.8536322 0.8688748 0.6702063 0.7065975 0.8048468 0.9078219
#> [22] 0.9370351 0.9607229 0.1836751 0.5680541 0.8762306 0.9078219 0.9078219
#> [29] 0.7742336 0.7266528 0.9875161 0.8651050 0.9307507 0.9339085 0.6022021
#> [36] 0.4650823 0.3593638 0.8096780 0.3853084 0.6370482 0.4968878 0.7388518
#> [43] 0.8905128 0.8536322 0.5805946 0.7627848 0.5276025 0.9078219 0.4264987
#> [50] 0.9607229 0.8144041 0.7509216 0.9950828 0.8190644 0.7135773 0.4264987
#> [57] 0.8536322 0.6022021 0.3853084 0.5124870 0.8798805 0.9009493 0.9823738
#> [64] 0.6777309 0.9900723 0.9607229 0.7388518 0.9431526 0.6022021 0.9950828
#> [71] 0.6022021 0.7899992 0.8974962 0.9607229 0.9370351 0.7950740 0.9797421
#> [78] 0.8453812 0.9900723 0.6777309 0.5918114 0.8411252 0.8325679 0.3191026
#> [85] 0.6923365 0.7950740 0.7742336 0.7266528 0.8834907 0.7135773 0.8236429
#> [92] 0.5417931 0.9770912 0.8453812 0.9431526 0.9550025 0.9210701 0.9823738
#> [99] 0.8905128 0.9717315 0.8325679 0.9550025 0.9243567 0.8834907 0.9431526
#> [106] 0.9717315 0.8725588 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [183] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [190] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#>
#> $Time
#> 128 24 41 63 170 66 43 24.1 88 108 61 14 68
#> 20.35 23.89 18.02 22.77 19.54 22.13 12.10 23.89 18.37 18.29 10.12 12.89 20.62
#> 79 150 125 29 158 58 30 177 52 187 24.2 136 133
#> 16.23 20.33 15.65 15.45 20.14 19.34 17.43 12.53 10.42 9.92 23.89 21.83 14.65
#> 177.1 177.2 51 97 25 167 107 159 36 63.1 164 106 69
#> 12.53 12.53 18.23 19.14 6.32 15.55 11.18 10.55 21.19 22.77 23.60 16.67 23.23
#> 190 15 8 81 125.1 197 108.1 194 177.3 113 187.1 171 88.1
#> 20.81 22.68 18.43 14.06 15.65 21.60 18.29 22.40 12.53 22.86 9.92 16.57 18.37
#> 127 130 76 113.1 125.2 99 69.1 169 57 14.1 77 166 91
#> 3.53 16.47 19.22 22.86 15.65 21.19 23.23 22.41 14.46 12.89 7.27 19.98 5.33
#> 187.2 8.1 93 99.1 127.1 99.2 134 123 187.3 52.1 111 149 26
#> 9.92 18.43 10.33 21.19 3.53 21.19 17.81 13.00 9.92 10.42 17.45 8.37 15.77
#> 91.1 166.1 153 100 188 168 105 111.1 51.1 97.1 13 76.1 181
#> 5.33 19.98 21.33 16.07 16.16 23.72 19.75 17.45 18.23 19.14 14.34 19.22 16.46
#> 66.1 16 26.1 93.1 145 49 77.1 81.1 183 188.1 145.1 43.1 13.1
#> 22.13 8.71 15.77 10.33 10.07 12.19 7.27 14.06 9.24 16.16 10.07 12.10 14.34
#> 93.2 183.1 180 121 165 9 104 144 9.1 103 152 147 151
#> 10.33 9.24 14.82 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72 103.1 147.1 156 198 22 82 152.1 95 118 1 2 126
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 122 135 185 182 151.1 174 54 71 47 53 22.1 137 84
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165.1 141 1.1 174.1 46 35 172 118.1 121.1 196 191 95.1 176
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98 173 46.1 118.2 186 87 152.2 109 160 122.1 94 72.1 186.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72.2 98.1 109.1 173.1 160.1 82.1 173.2 2.1 87.1 151.2 75 172.1 34
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 147.2 2.2 54.1 178 9.2 75.1 138 152.3 120 163 7 191.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[47]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.00319657 0.24346504 0.60510744
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.7518943 0.0145514 -0.1738792
#> grade_iii, Cure model
#> 0.7742045
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 41 18.02 1 40 1 0
#> 50 10.02 1 NA 1 0
#> 76 19.22 1 54 0 1
#> 175 21.91 1 43 0 0
#> 181 16.46 1 45 0 1
#> 106 16.67 1 49 1 0
#> 194 22.40 1 38 0 1
#> 175.1 21.91 1 43 0 0
#> 90 20.94 1 50 0 1
#> 139 21.49 1 63 1 0
#> 6 15.64 1 39 0 0
#> 125 15.65 1 67 1 0
#> 14 12.89 1 21 0 0
#> 79 16.23 1 54 1 0
#> 39 15.59 1 37 0 1
#> 133 14.65 1 57 0 0
#> 45 17.42 1 54 0 1
#> 159 10.55 1 50 0 1
#> 92 22.92 1 47 0 1
#> 99 21.19 1 38 0 1
#> 42 12.43 1 49 0 1
#> 88 18.37 1 47 0 0
#> 171 16.57 1 41 0 1
#> 86 23.81 1 58 0 1
#> 106.1 16.67 1 49 1 0
#> 157 15.10 1 47 0 0
#> 192 16.44 1 31 1 0
#> 108 18.29 1 39 0 1
#> 90.1 20.94 1 50 0 1
#> 164 23.60 1 76 0 1
#> 155 13.08 1 26 0 0
#> 24 23.89 1 38 0 0
#> 63 22.77 1 31 1 0
#> 91 5.33 1 61 0 1
#> 4 17.64 1 NA 0 1
#> 57 14.46 1 45 0 1
#> 113 22.86 1 34 0 0
#> 166 19.98 1 48 0 0
#> 159.1 10.55 1 50 0 1
#> 76.1 19.22 1 54 0 1
#> 183 9.24 1 67 1 0
#> 170 19.54 1 43 0 1
#> 125.1 15.65 1 67 1 0
#> 93 10.33 1 52 0 1
#> 13 14.34 1 54 0 1
#> 171.1 16.57 1 41 0 1
#> 189 10.51 1 NA 1 0
#> 61 10.12 1 36 0 1
#> 171.2 16.57 1 41 0 1
#> 96 14.54 1 33 0 1
#> 149 8.37 1 33 1 0
#> 123 13.00 1 44 1 0
#> 177 12.53 1 75 0 0
#> 175.2 21.91 1 43 0 0
#> 59 10.16 1 NA 1 0
#> 188 16.16 1 46 0 1
#> 187 9.92 1 39 1 0
#> 195 11.76 1 NA 1 0
#> 159.2 10.55 1 50 0 1
#> 30 17.43 1 78 0 0
#> 85 16.44 1 36 0 0
#> 13.1 14.34 1 54 0 1
#> 171.3 16.57 1 41 0 1
#> 113.1 22.86 1 34 0 0
#> 158 20.14 1 74 1 0
#> 130 16.47 1 53 0 1
#> 129 23.41 1 53 1 0
#> 150 20.33 1 48 0 0
#> 168 23.72 1 70 0 0
#> 6.1 15.64 1 39 0 0
#> 81 14.06 1 34 0 0
#> 145 10.07 1 65 1 0
#> 50.1 10.02 1 NA 1 0
#> 14.1 12.89 1 21 0 0
#> 128 20.35 1 35 0 1
#> 158.1 20.14 1 74 1 0
#> 159.3 10.55 1 50 0 1
#> 197 21.60 1 69 1 0
#> 91.1 5.33 1 61 0 1
#> 159.4 10.55 1 50 0 1
#> 55 19.34 1 69 0 1
#> 16 8.71 1 71 0 1
#> 139.1 21.49 1 63 1 0
#> 63.1 22.77 1 31 1 0
#> 125.2 15.65 1 67 1 0
#> 63.2 22.77 1 31 1 0
#> 41.1 18.02 1 40 1 0
#> 181.1 16.46 1 45 0 1
#> 26 15.77 1 49 0 1
#> 36 21.19 1 48 0 1
#> 127 3.53 1 62 0 1
#> 61.1 10.12 1 36 0 1
#> 175.3 21.91 1 43 0 0
#> 113.2 22.86 1 34 0 0
#> 101 9.97 1 10 0 1
#> 90.2 20.94 1 50 0 1
#> 5 16.43 1 51 0 1
#> 96.1 14.54 1 33 0 1
#> 16.1 8.71 1 71 0 1
#> 29 15.45 1 68 1 0
#> 197.1 21.60 1 69 1 0
#> 77 7.27 1 67 0 1
#> 105 19.75 1 60 0 0
#> 179 18.63 1 42 0 0
#> 110 17.56 1 65 0 1
#> 129.1 23.41 1 53 1 0
#> 26.1 15.77 1 49 0 1
#> 111 17.45 1 47 0 1
#> 180 14.82 1 37 0 0
#> 195.1 11.76 1 NA 1 0
#> 113.3 22.86 1 34 0 0
#> 184 17.77 1 38 0 0
#> 104 24.00 0 50 1 0
#> 54 24.00 0 53 1 0
#> 71 24.00 0 51 0 0
#> 17 24.00 0 38 0 1
#> 46 24.00 0 71 0 0
#> 7 24.00 0 37 1 0
#> 174 24.00 0 49 1 0
#> 178 24.00 0 52 1 0
#> 176 24.00 0 43 0 1
#> 172 24.00 0 41 0 0
#> 72 24.00 0 40 0 1
#> 156 24.00 0 50 1 0
#> 47 24.00 0 38 0 1
#> 119 24.00 0 17 0 0
#> 19 24.00 0 57 0 1
#> 148 24.00 0 61 1 0
#> 103 24.00 0 56 1 0
#> 17.1 24.00 0 38 0 1
#> 102 24.00 0 49 0 0
#> 12 24.00 0 63 0 0
#> 95 24.00 0 68 0 1
#> 198 24.00 0 66 0 1
#> 178.1 24.00 0 52 1 0
#> 142 24.00 0 53 0 0
#> 148.1 24.00 0 61 1 0
#> 38 24.00 0 31 1 0
#> 182 24.00 0 35 0 0
#> 165 24.00 0 47 0 0
#> 2 24.00 0 9 0 0
#> 162 24.00 0 51 0 0
#> 31 24.00 0 36 0 1
#> 160 24.00 0 31 1 0
#> 163 24.00 0 66 0 0
#> 71.1 24.00 0 51 0 0
#> 173 24.00 0 19 0 1
#> 48 24.00 0 31 1 0
#> 11 24.00 0 42 0 1
#> 95.1 24.00 0 68 0 1
#> 176.1 24.00 0 43 0 1
#> 12.1 24.00 0 63 0 0
#> 7.1 24.00 0 37 1 0
#> 102.1 24.00 0 49 0 0
#> 200 24.00 0 64 0 0
#> 80 24.00 0 41 0 0
#> 118 24.00 0 44 1 0
#> 65 24.00 0 57 1 0
#> 74 24.00 0 43 0 1
#> 71.2 24.00 0 51 0 0
#> 160.1 24.00 0 31 1 0
#> 138 24.00 0 44 1 0
#> 82 24.00 0 34 0 0
#> 118.1 24.00 0 44 1 0
#> 182.1 24.00 0 35 0 0
#> 176.2 24.00 0 43 0 1
#> 54.1 24.00 0 53 1 0
#> 144 24.00 0 28 0 1
#> 147 24.00 0 76 1 0
#> 173.1 24.00 0 19 0 1
#> 71.3 24.00 0 51 0 0
#> 146 24.00 0 63 1 0
#> 137 24.00 0 45 1 0
#> 48.1 24.00 0 31 1 0
#> 1 24.00 0 23 1 0
#> 193 24.00 0 45 0 1
#> 74.1 24.00 0 43 0 1
#> 67 24.00 0 25 0 0
#> 176.3 24.00 0 43 0 1
#> 112 24.00 0 61 0 0
#> 83 24.00 0 6 0 0
#> 200.1 24.00 0 64 0 0
#> 119.1 24.00 0 17 0 0
#> 132 24.00 0 55 0 0
#> 72.1 24.00 0 40 0 1
#> 146.1 24.00 0 63 1 0
#> 7.2 24.00 0 37 1 0
#> 132.1 24.00 0 55 0 0
#> 191 24.00 0 60 0 1
#> 186 24.00 0 45 1 0
#> 87 24.00 0 27 0 0
#> 198.1 24.00 0 66 0 1
#> 62 24.00 0 71 0 0
#> 118.2 24.00 0 44 1 0
#> 176.4 24.00 0 43 0 1
#> 118.3 24.00 0 44 1 0
#> 126 24.00 0 48 0 0
#> 186.1 24.00 0 45 1 0
#> 95.2 24.00 0 68 0 1
#> 1.1 24.00 0 23 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.752 NA NA NA
#> 2 age, Cure model 0.0146 NA NA NA
#> 3 grade_ii, Cure model -0.174 NA NA NA
#> 4 grade_iii, Cure model 0.774 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00320 NA NA NA
#> 2 grade_ii, Survival model 0.243 NA NA NA
#> 3 grade_iii, Survival model 0.605 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.75189 0.01455 -0.17388 0.77420
#>
#> Degrees of Freedom: 192 Total (i.e. Null); 189 Residual
#> Null Deviance: 266.1
#> Residual Deviance: 255.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.7518943 0.0145514 -0.1738792 0.7742045
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.00319657 0.24346504 0.60510744
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.467487228 0.419378544 0.199872214 0.595603695 0.533515371 0.188485825
#> [7] 0.199872214 0.309173291 0.265346369 0.697433640 0.672543692 0.821313091
#> [13] 0.638690486 0.714174216 0.747636326 0.524196473 0.853806989 0.098562937
#> [19] 0.287756598 0.845688504 0.448177294 0.551932608 0.028610669 0.533515371
#> [25] 0.730887910 0.612847642 0.457895035 0.309173291 0.059208474 0.805031845
#> [31] 0.009250009 0.155175308 0.977412353 0.772493027 0.111066622 0.379123527
#> [37] 0.853806989 0.419378544 0.939182606 0.399437176 0.672543692 0.892619704
#> [43] 0.780716487 0.551932608 0.900482545 0.551932608 0.756031499 0.962147258
#> [49] 0.813176880 0.837525674 0.199872214 0.647292138 0.931466984 0.853806989
#> [55] 0.514787070 0.612847642 0.780716487 0.551932608 0.111066622 0.359201753
#> [61] 0.586767379 0.073437811 0.349094987 0.043345883 0.697433640 0.796893378
#> [67] 0.915969302 0.821313091 0.339029688 0.359201753 0.853806989 0.242855687
#> [73] 0.977412353 0.853806989 0.409464777 0.946896344 0.265346369 0.155175308
#> [79] 0.672543692 0.155175308 0.467487228 0.595603695 0.655827889 0.287756598
#> [85] 0.992470794 0.900482545 0.199872214 0.111066622 0.923743292 0.309173291
#> [91] 0.630080322 0.756031499 0.946896344 0.722532340 0.242855687 0.969794173
#> [97] 0.389257219 0.438488865 0.495942716 0.073437811 0.655827889 0.505415473
#> [103] 0.739256827 0.111066622 0.486380869 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [193] 0.000000000
#>
#> $Time
#> 41 76 175 181 106 194 175.1 90 139 6 125 14 79
#> 18.02 19.22 21.91 16.46 16.67 22.40 21.91 20.94 21.49 15.64 15.65 12.89 16.23
#> 39 133 45 159 92 99 42 88 171 86 106.1 157 192
#> 15.59 14.65 17.42 10.55 22.92 21.19 12.43 18.37 16.57 23.81 16.67 15.10 16.44
#> 108 90.1 164 155 24 63 91 57 113 166 159.1 76.1 183
#> 18.29 20.94 23.60 13.08 23.89 22.77 5.33 14.46 22.86 19.98 10.55 19.22 9.24
#> 170 125.1 93 13 171.1 61 171.2 96 149 123 177 175.2 188
#> 19.54 15.65 10.33 14.34 16.57 10.12 16.57 14.54 8.37 13.00 12.53 21.91 16.16
#> 187 159.2 30 85 13.1 171.3 113.1 158 130 129 150 168 6.1
#> 9.92 10.55 17.43 16.44 14.34 16.57 22.86 20.14 16.47 23.41 20.33 23.72 15.64
#> 81 145 14.1 128 158.1 159.3 197 91.1 159.4 55 16 139.1 63.1
#> 14.06 10.07 12.89 20.35 20.14 10.55 21.60 5.33 10.55 19.34 8.71 21.49 22.77
#> 125.2 63.2 41.1 181.1 26 36 127 61.1 175.3 113.2 101 90.2 5
#> 15.65 22.77 18.02 16.46 15.77 21.19 3.53 10.12 21.91 22.86 9.97 20.94 16.43
#> 96.1 16.1 29 197.1 77 105 179 110 129.1 26.1 111 180 113.3
#> 14.54 8.71 15.45 21.60 7.27 19.75 18.63 17.56 23.41 15.77 17.45 14.82 22.86
#> 184 104 54 71 17 46 7 174 178 176 172 72 156
#> 17.77 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 47 119 19 148 103 17.1 102 12 95 198 178.1 142 148.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 38 182 165 2 162 31 160 163 71.1 173 48 11 95.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176.1 12.1 7.1 102.1 200 80 118 65 74 71.2 160.1 138 82
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 118.1 182.1 176.2 54.1 144 147 173.1 71.3 146 137 48.1 1 193
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 74.1 67 176.3 112 83 200.1 119.1 132 72.1 146.1 7.2 132.1 191
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186 87 198.1 62 118.2 176.4 118.3 126 186.1 95.2 1.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[48]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.0123749 0.9034978 0.6674528
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.77538825 0.01386822 0.26248072
#> grade_iii, Cure model
#> 0.59910647
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 153 21.33 1 55 1 0
#> 59 10.16 1 NA 1 0
#> 15 22.68 1 48 0 0
#> 157 15.10 1 47 0 0
#> 177 12.53 1 75 0 0
#> 77 7.27 1 67 0 1
#> 169 22.41 1 46 0 0
#> 40 18.00 1 28 1 0
#> 57 14.46 1 45 0 1
#> 164 23.60 1 76 0 1
#> 136 21.83 1 43 0 1
#> 164.1 23.60 1 76 0 1
#> 79 16.23 1 54 1 0
#> 101 9.97 1 10 0 1
#> 134 17.81 1 47 1 0
#> 25 6.32 1 34 1 0
#> 113 22.86 1 34 0 0
#> 8 18.43 1 32 0 0
#> 158 20.14 1 74 1 0
#> 88 18.37 1 47 0 0
#> 113.1 22.86 1 34 0 0
#> 15.1 22.68 1 48 0 0
#> 23 16.92 1 61 0 0
#> 159 10.55 1 50 0 1
#> 168 23.72 1 70 0 0
#> 130 16.47 1 53 0 1
#> 57.1 14.46 1 45 0 1
#> 40.1 18.00 1 28 1 0
#> 107 11.18 1 54 1 0
#> 15.2 22.68 1 48 0 0
#> 24 23.89 1 38 0 0
#> 164.2 23.60 1 76 0 1
#> 29 15.45 1 68 1 0
#> 6 15.64 1 39 0 0
#> 140 12.68 1 59 1 0
#> 43 12.10 1 61 0 1
#> 192 16.44 1 31 1 0
#> 100 16.07 1 60 0 0
#> 92 22.92 1 47 0 1
#> 99 21.19 1 38 0 1
#> 92.1 22.92 1 47 0 1
#> 79.1 16.23 1 54 1 0
#> 128 20.35 1 35 0 1
#> 105 19.75 1 60 0 0
#> 168.1 23.72 1 70 0 0
#> 140.1 12.68 1 59 1 0
#> 114 13.68 1 NA 0 0
#> 96 14.54 1 33 0 1
#> 195 11.76 1 NA 1 0
#> 39 15.59 1 37 0 1
#> 199 19.81 1 NA 0 1
#> 158.1 20.14 1 74 1 0
#> 16 8.71 1 71 0 1
#> 93 10.33 1 52 0 1
#> 124 9.73 1 NA 1 0
#> 149 8.37 1 33 1 0
#> 81 14.06 1 34 0 0
#> 192.1 16.44 1 31 1 0
#> 97 19.14 1 65 0 1
#> 195.1 11.76 1 NA 1 0
#> 159.1 10.55 1 50 0 1
#> 29.1 15.45 1 68 1 0
#> 171 16.57 1 41 0 1
#> 70 7.38 1 30 1 0
#> 124.1 9.73 1 NA 1 0
#> 5 16.43 1 51 0 1
#> 177.1 12.53 1 75 0 0
#> 123 13.00 1 44 1 0
#> 128.1 20.35 1 35 0 1
#> 194 22.40 1 38 0 1
#> 168.2 23.72 1 70 0 0
#> 8.1 18.43 1 32 0 0
#> 166 19.98 1 48 0 0
#> 106 16.67 1 49 1 0
#> 128.2 20.35 1 35 0 1
#> 113.2 22.86 1 34 0 0
#> 153.1 21.33 1 55 1 0
#> 175 21.91 1 43 0 0
#> 63 22.77 1 31 1 0
#> 29.2 15.45 1 68 1 0
#> 124.2 9.73 1 NA 1 0
#> 130.1 16.47 1 53 0 1
#> 29.3 15.45 1 68 1 0
#> 90 20.94 1 50 0 1
#> 56 12.21 1 60 0 0
#> 113.3 22.86 1 34 0 0
#> 50 10.02 1 NA 1 0
#> 36 21.19 1 48 0 1
#> 57.2 14.46 1 45 0 1
#> 114.1 13.68 1 NA 0 0
#> 107.1 11.18 1 54 1 0
#> 189 10.51 1 NA 1 0
#> 57.3 14.46 1 45 0 1
#> 101.1 9.97 1 10 0 1
#> 6.1 15.64 1 39 0 0
#> 192.2 16.44 1 31 1 0
#> 179 18.63 1 42 0 0
#> 159.2 10.55 1 50 0 1
#> 6.2 15.64 1 39 0 0
#> 93.1 10.33 1 52 0 1
#> 78 23.88 1 43 0 0
#> 129 23.41 1 53 1 0
#> 76 19.22 1 54 0 1
#> 15.3 22.68 1 48 0 0
#> 91 5.33 1 61 0 1
#> 6.3 15.64 1 39 0 0
#> 58 19.34 1 39 0 0
#> 97.1 19.14 1 65 0 1
#> 32 20.90 1 37 1 0
#> 88.1 18.37 1 47 0 0
#> 4 17.64 1 NA 0 1
#> 154 12.63 1 20 1 0
#> 65 24.00 0 57 1 0
#> 121 24.00 0 57 1 0
#> 82 24.00 0 34 0 0
#> 109 24.00 0 48 0 0
#> 156 24.00 0 50 1 0
#> 67 24.00 0 25 0 0
#> 38 24.00 0 31 1 0
#> 62 24.00 0 71 0 0
#> 163 24.00 0 66 0 0
#> 102 24.00 0 49 0 0
#> 82.1 24.00 0 34 0 0
#> 21 24.00 0 47 0 0
#> 75 24.00 0 21 1 0
#> 94 24.00 0 51 0 1
#> 11 24.00 0 42 0 1
#> 160 24.00 0 31 1 0
#> 142 24.00 0 53 0 0
#> 173 24.00 0 19 0 1
#> 46 24.00 0 71 0 0
#> 84 24.00 0 39 0 1
#> 112 24.00 0 61 0 0
#> 144 24.00 0 28 0 1
#> 98 24.00 0 34 1 0
#> 64 24.00 0 43 0 0
#> 115 24.00 0 NA 1 0
#> 98.1 24.00 0 34 1 0
#> 165 24.00 0 47 0 0
#> 75.1 24.00 0 21 1 0
#> 48 24.00 0 31 1 0
#> 191 24.00 0 60 0 1
#> 182 24.00 0 35 0 0
#> 80 24.00 0 41 0 0
#> 83 24.00 0 6 0 0
#> 120 24.00 0 68 0 1
#> 3 24.00 0 31 1 0
#> 160.1 24.00 0 31 1 0
#> 62.1 24.00 0 71 0 0
#> 182.1 24.00 0 35 0 0
#> 46.1 24.00 0 71 0 0
#> 34 24.00 0 36 0 0
#> 95 24.00 0 68 0 1
#> 109.1 24.00 0 48 0 0
#> 46.2 24.00 0 71 0 0
#> 9 24.00 0 31 1 0
#> 174 24.00 0 49 1 0
#> 151 24.00 0 42 0 0
#> 156.1 24.00 0 50 1 0
#> 94.1 24.00 0 51 0 1
#> 191.1 24.00 0 60 0 1
#> 198 24.00 0 66 0 1
#> 35 24.00 0 51 0 0
#> 198.1 24.00 0 66 0 1
#> 34.1 24.00 0 36 0 0
#> 84.1 24.00 0 39 0 1
#> 173.1 24.00 0 19 0 1
#> 9.1 24.00 0 31 1 0
#> 54 24.00 0 53 1 0
#> 38.1 24.00 0 31 1 0
#> 84.2 24.00 0 39 0 1
#> 131 24.00 0 66 0 0
#> 62.2 24.00 0 71 0 0
#> 20 24.00 0 46 1 0
#> 74 24.00 0 43 0 1
#> 2 24.00 0 9 0 0
#> 152 24.00 0 36 0 1
#> 193 24.00 0 45 0 1
#> 21.1 24.00 0 47 0 0
#> 82.2 24.00 0 34 0 0
#> 72 24.00 0 40 0 1
#> 82.3 24.00 0 34 0 0
#> 62.3 24.00 0 71 0 0
#> 186 24.00 0 45 1 0
#> 17 24.00 0 38 0 1
#> 174.1 24.00 0 49 1 0
#> 172 24.00 0 41 0 0
#> 82.4 24.00 0 34 0 0
#> 112.1 24.00 0 61 0 0
#> 104 24.00 0 50 1 0
#> 95.1 24.00 0 68 0 1
#> 172.1 24.00 0 41 0 0
#> 20.1 24.00 0 46 1 0
#> 27 24.00 0 63 1 0
#> 137 24.00 0 45 1 0
#> 165.1 24.00 0 47 0 0
#> 27.1 24.00 0 63 1 0
#> 173.2 24.00 0 19 0 1
#> 144.1 24.00 0 28 0 1
#> 62.4 24.00 0 71 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.775 NA NA NA
#> 2 age, Cure model 0.0139 NA NA NA
#> 3 grade_ii, Cure model 0.262 NA NA NA
#> 4 grade_iii, Cure model 0.599 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0124 NA NA NA
#> 2 grade_ii, Survival model 0.903 NA NA NA
#> 3 grade_iii, Survival model 0.667 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.77539 0.01387 0.26248 0.59911
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 258.3
#> Residual Deviance: 253.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.77538825 0.01386822 0.26248072 0.59910647
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.0123749 0.9034978 0.6674528
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.2117791502 0.1270904195 0.6928051238 0.8060334683 0.9699274757
#> [6] 0.1667315203 0.4432650434 0.7137974565 0.0286889066 0.2004869784
#> [11] 0.0286889066 0.5697712403 0.9193315662 0.4646950518 0.9799913114
#> [16] 0.0811397762 0.3993094790 0.3052365394 0.4210342531 0.0811397762
#> [21] 0.1270904195 0.4754413388 0.8680932724 0.0085317728 0.5078635219
#> [26] 0.7137974565 0.4432650434 0.8474817647 0.1270904195 0.0007546258
#> [31] 0.0286889066 0.6519438572 0.6002744558 0.7753200096 0.8370448505
#> [36] 0.5291307136 0.5899858693 0.0636106985 0.2332084924 0.0636106985
#> [41] 0.5697712403 0.2756713252 0.3356301451 0.0085317728 0.7753200096
#> [46] 0.7033244506 0.6414363370 0.3052365394 0.9395641248 0.8987721877
#> [51] 0.9497564643 0.7545039480 0.5291307136 0.3673886488 0.8680932724
#> [56] 0.6519438572 0.4971109745 0.9598792041 0.5594749302 0.8060334683
#> [61] 0.7649425586 0.2756713252 0.1779932674 0.0085317728 0.3993094790
#> [66] 0.3252958939 0.4863179086 0.2756713252 0.0811397762 0.2117791502
#> [71] 0.1891020761 0.1173381687 0.6519438572 0.5078635219 0.6519438572
#> [76] 0.2543535544 0.8266188194 0.0811397762 0.2332084924 0.7137974565
#> [81] 0.8474817647 0.7137974565 0.9193315662 0.6002744558 0.5291307136
#> [86] 0.3884904854 0.8680932724 0.6002744558 0.8987721877 0.0037391379
#> [91] 0.0539017465 0.3567611390 0.1270904195 0.9899914241 0.6002744558
#> [96] 0.3461339032 0.3673886488 0.2651326766 0.4210342531 0.7958327893
#> [101] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000
#>
#> $Time
#> 153 15 157 177 77 169 40 57 164 136 164.1 79 101
#> 21.33 22.68 15.10 12.53 7.27 22.41 18.00 14.46 23.60 21.83 23.60 16.23 9.97
#> 134 25 113 8 158 88 113.1 15.1 23 159 168 130 57.1
#> 17.81 6.32 22.86 18.43 20.14 18.37 22.86 22.68 16.92 10.55 23.72 16.47 14.46
#> 40.1 107 15.2 24 164.2 29 6 140 43 192 100 92 99
#> 18.00 11.18 22.68 23.89 23.60 15.45 15.64 12.68 12.10 16.44 16.07 22.92 21.19
#> 92.1 79.1 128 105 168.1 140.1 96 39 158.1 16 93 149 81
#> 22.92 16.23 20.35 19.75 23.72 12.68 14.54 15.59 20.14 8.71 10.33 8.37 14.06
#> 192.1 97 159.1 29.1 171 70 5 177.1 123 128.1 194 168.2 8.1
#> 16.44 19.14 10.55 15.45 16.57 7.38 16.43 12.53 13.00 20.35 22.40 23.72 18.43
#> 166 106 128.2 113.2 153.1 175 63 29.2 130.1 29.3 90 56 113.3
#> 19.98 16.67 20.35 22.86 21.33 21.91 22.77 15.45 16.47 15.45 20.94 12.21 22.86
#> 36 57.2 107.1 57.3 101.1 6.1 192.2 179 159.2 6.2 93.1 78 129
#> 21.19 14.46 11.18 14.46 9.97 15.64 16.44 18.63 10.55 15.64 10.33 23.88 23.41
#> 76 15.3 91 6.3 58 97.1 32 88.1 154 65 121 82 109
#> 19.22 22.68 5.33 15.64 19.34 19.14 20.90 18.37 12.63 24.00 24.00 24.00 24.00
#> 156 67 38 62 163 102 82.1 21 75 94 11 160 142
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 173 46 84 112 144 98 64 98.1 165 75.1 48 191 182
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80 83 120 3 160.1 62.1 182.1 46.1 34 95 109.1 46.2 9
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174 151 156.1 94.1 191.1 198 35 198.1 34.1 84.1 173.1 9.1 54
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 38.1 84.2 131 62.2 20 74 2 152 193 21.1 82.2 72 82.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62.3 186 17 174.1 172 82.4 112.1 104 95.1 172.1 20.1 27 137
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165.1 27.1 173.2 144.1 62.4
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[49]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.008385176 0.529248393 0.266034771
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.86086512 0.01500494 0.10123472
#> grade_iii, Cure model
#> 1.02863982
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 79 16.23 1 54 1 0
#> 168 23.72 1 70 0 0
#> 129 23.41 1 53 1 0
#> 107 11.18 1 54 1 0
#> 164 23.60 1 76 0 1
#> 32 20.90 1 37 1 0
#> 93 10.33 1 52 0 1
#> 164.1 23.60 1 76 0 1
#> 167 15.55 1 56 1 0
#> 175 21.91 1 43 0 0
#> 55 19.34 1 69 0 1
#> 79.1 16.23 1 54 1 0
#> 180 14.82 1 37 0 0
#> 153 21.33 1 55 1 0
#> 23 16.92 1 61 0 0
#> 79.2 16.23 1 54 1 0
#> 59 10.16 1 NA 1 0
#> 58 19.34 1 39 0 0
#> 63 22.77 1 31 1 0
#> 29 15.45 1 68 1 0
#> 15 22.68 1 48 0 0
#> 13 14.34 1 54 0 1
#> 4 17.64 1 NA 0 1
#> 134 17.81 1 47 1 0
#> 24 23.89 1 38 0 0
#> 10 10.53 1 34 0 0
#> 113 22.86 1 34 0 0
#> 188 16.16 1 46 0 1
#> 23.1 16.92 1 61 0 0
#> 128 20.35 1 35 0 1
#> 171 16.57 1 41 0 1
#> 158 20.14 1 74 1 0
#> 157 15.10 1 47 0 0
#> 15.1 22.68 1 48 0 0
#> 107.1 11.18 1 54 1 0
#> 56 12.21 1 60 0 0
#> 4.1 17.64 1 NA 0 1
#> 190 20.81 1 42 1 0
#> 110 17.56 1 65 0 1
#> 77 7.27 1 67 0 1
#> 125 15.65 1 67 1 0
#> 133 14.65 1 57 0 0
#> 70 7.38 1 30 1 0
#> 15.2 22.68 1 48 0 0
#> 159 10.55 1 50 0 1
#> 92 22.92 1 47 0 1
#> 69 23.23 1 25 0 1
#> 181 16.46 1 45 0 1
#> 154 12.63 1 20 1 0
#> 93.1 10.33 1 52 0 1
#> 45 17.42 1 54 0 1
#> 23.2 16.92 1 61 0 0
#> 68 20.62 1 44 0 0
#> 89 11.44 1 NA 0 0
#> 125.1 15.65 1 67 1 0
#> 107.2 11.18 1 54 1 0
#> 78 23.88 1 43 0 0
#> 157.1 15.10 1 47 0 0
#> 86 23.81 1 58 0 1
#> 189 10.51 1 NA 1 0
#> 42 12.43 1 49 0 1
#> 183 9.24 1 67 1 0
#> 45.1 17.42 1 54 0 1
#> 179 18.63 1 42 0 0
#> 140 12.68 1 59 1 0
#> 86.1 23.81 1 58 0 1
#> 171.1 16.57 1 41 0 1
#> 14 12.89 1 21 0 0
#> 40 18.00 1 28 1 0
#> 56.1 12.21 1 60 0 0
#> 199 19.81 1 NA 0 1
#> 110.1 17.56 1 65 0 1
#> 171.2 16.57 1 41 0 1
#> 125.2 15.65 1 67 1 0
#> 55.1 19.34 1 69 0 1
#> 40.1 18.00 1 28 1 0
#> 145 10.07 1 65 1 0
#> 29.1 15.45 1 68 1 0
#> 55.2 19.34 1 69 0 1
#> 111 17.45 1 47 0 1
#> 117 17.46 1 26 0 1
#> 133.1 14.65 1 57 0 0
#> 123 13.00 1 44 1 0
#> 168.1 23.72 1 70 0 0
#> 68.1 20.62 1 44 0 0
#> 66 22.13 1 53 0 0
#> 56.2 12.21 1 60 0 0
#> 55.3 19.34 1 69 0 1
#> 187 9.92 1 39 1 0
#> 61 10.12 1 36 0 1
#> 197 21.60 1 69 1 0
#> 59.1 10.16 1 NA 1 0
#> 158.1 20.14 1 74 1 0
#> 99 21.19 1 38 0 1
#> 57 14.46 1 45 0 1
#> 90 20.94 1 50 0 1
#> 23.3 16.92 1 61 0 0
#> 106 16.67 1 49 1 0
#> 181.1 16.46 1 45 0 1
#> 130 16.47 1 53 0 1
#> 153.1 21.33 1 55 1 0
#> 61.1 10.12 1 36 0 1
#> 117.1 17.46 1 26 0 1
#> 164.2 23.60 1 76 0 1
#> 61.2 10.12 1 36 0 1
#> 154.1 12.63 1 20 1 0
#> 139 21.49 1 63 1 0
#> 63.1 22.77 1 31 1 0
#> 68.2 20.62 1 44 0 0
#> 155 13.08 1 26 0 0
#> 155.1 13.08 1 26 0 0
#> 57.1 14.46 1 45 0 1
#> 156 24.00 0 50 1 0
#> 31 24.00 0 36 0 1
#> 28 24.00 0 67 1 0
#> 152 24.00 0 36 0 1
#> 132 24.00 0 55 0 0
#> 191 24.00 0 60 0 1
#> 118 24.00 0 44 1 0
#> 12 24.00 0 63 0 0
#> 131 24.00 0 66 0 0
#> 104 24.00 0 50 1 0
#> 163 24.00 0 66 0 0
#> 163.1 24.00 0 66 0 0
#> 131.1 24.00 0 66 0 0
#> 53 24.00 0 32 0 1
#> 12.1 24.00 0 63 0 0
#> 84 24.00 0 39 0 1
#> 3 24.00 0 31 1 0
#> 48 24.00 0 31 1 0
#> 87 24.00 0 27 0 0
#> 178 24.00 0 52 1 0
#> 65 24.00 0 57 1 0
#> 138 24.00 0 44 1 0
#> 162 24.00 0 51 0 0
#> 148 24.00 0 61 1 0
#> 143 24.00 0 51 0 0
#> 161 24.00 0 45 0 0
#> 162.1 24.00 0 51 0 0
#> 3.1 24.00 0 31 1 0
#> 120 24.00 0 68 0 1
#> 33 24.00 0 53 0 0
#> 102 24.00 0 49 0 0
#> 94 24.00 0 51 0 1
#> 38 24.00 0 31 1 0
#> 142 24.00 0 53 0 0
#> 94.1 24.00 0 51 0 1
#> 163.2 24.00 0 66 0 0
#> 162.2 24.00 0 51 0 0
#> 160 24.00 0 31 1 0
#> 146 24.00 0 63 1 0
#> 64 24.00 0 43 0 0
#> 65.1 24.00 0 57 1 0
#> 31.1 24.00 0 36 0 1
#> 83 24.00 0 6 0 0
#> 160.1 24.00 0 31 1 0
#> 48.1 24.00 0 31 1 0
#> 80 24.00 0 41 0 0
#> 48.2 24.00 0 31 1 0
#> 71 24.00 0 51 0 0
#> 53.1 24.00 0 32 0 1
#> 65.2 24.00 0 57 1 0
#> 141 24.00 0 44 1 0
#> 121 24.00 0 57 1 0
#> 148.1 24.00 0 61 1 0
#> 65.3 24.00 0 57 1 0
#> 185 24.00 0 44 1 0
#> 116 24.00 0 58 0 1
#> 122 24.00 0 66 0 0
#> 31.2 24.00 0 36 0 1
#> 62 24.00 0 71 0 0
#> 141.1 24.00 0 44 1 0
#> 82 24.00 0 34 0 0
#> 9 24.00 0 31 1 0
#> 28.1 24.00 0 67 1 0
#> 82.1 24.00 0 34 0 0
#> 73 24.00 0 NA 0 1
#> 174 24.00 0 49 1 0
#> 138.1 24.00 0 44 1 0
#> 120.1 24.00 0 68 0 1
#> 33.1 24.00 0 53 0 0
#> 12.2 24.00 0 63 0 0
#> 53.2 24.00 0 32 0 1
#> 132.1 24.00 0 55 0 0
#> 143.1 24.00 0 51 0 0
#> 34 24.00 0 36 0 0
#> 12.3 24.00 0 63 0 0
#> 27 24.00 0 63 1 0
#> 186 24.00 0 45 1 0
#> 2 24.00 0 9 0 0
#> 87.1 24.00 0 27 0 0
#> 31.3 24.00 0 36 0 1
#> 200 24.00 0 64 0 0
#> 148.2 24.00 0 61 1 0
#> 71.1 24.00 0 51 0 0
#> 7 24.00 0 37 1 0
#> 48.3 24.00 0 31 1 0
#> 48.4 24.00 0 31 1 0
#> 144 24.00 0 28 0 1
#> 20 24.00 0 46 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.861 NA NA NA
#> 2 age, Cure model 0.0150 NA NA NA
#> 3 grade_ii, Cure model 0.101 NA NA NA
#> 4 grade_iii, Cure model 1.03 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00839 NA NA NA
#> 2 grade_ii, Survival model 0.529 NA NA NA
#> 3 grade_iii, Survival model 0.266 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.8609 0.0150 0.1012 1.0286
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.5
#> Residual Deviance: 254 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.86086512 0.01500494 0.10123472 1.02863982
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.008385176 0.529248393 0.266034771
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.541690572 0.022172188 0.058256534 0.841003114 0.035938674 0.206489995
#> [7] 0.893678250 0.035938674 0.612007237 0.142505416 0.279684776 0.541690572
#> [13] 0.662926621 0.170218383 0.431864746 0.541690572 0.279684776 0.092748034
#> [19] 0.622205344 0.108693053 0.714936656 0.354653495 0.001435135 0.883029885
#> [25] 0.083912595 0.571689300 0.431864746 0.251767105 0.481324376 0.261147115
#> [31] 0.642460881 0.108693053 0.841003114 0.809499621 0.215626581 0.364278879
#> [37] 0.989333155 0.581889558 0.673282688 0.978695678 0.108693053 0.872413277
#> [43] 0.075302654 0.066810354 0.521412370 0.778242421 0.893678250 0.412455795
#> [49] 0.431864746 0.224688850 0.581889558 0.841003114 0.005677495 0.642460881
#> [55] 0.011456399 0.799022594 0.968021065 0.412455795 0.325724615 0.767658129
#> [61] 0.011456399 0.481324376 0.757068710 0.335590160 0.809499621 0.364278879
#> [67] 0.481324376 0.581889558 0.279684776 0.335590160 0.946652657 0.622205344
#> [73] 0.279684776 0.402713510 0.383519773 0.673282688 0.746503155 0.022172188
#> [79] 0.224688850 0.133463008 0.809499621 0.279684776 0.957350222 0.914926813
#> [85] 0.151725057 0.261147115 0.188077978 0.694076739 0.197253435 0.431864746
#> [91] 0.471195448 0.521412370 0.511214959 0.170218383 0.914926813 0.383519773
#> [97] 0.035938674 0.914926813 0.778242421 0.160971908 0.092748034 0.224688850
#> [103] 0.725470200 0.725470200 0.694076739 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 79 168 129 107 164 32 93 164.1 167 175 55 79.1 180
#> 16.23 23.72 23.41 11.18 23.60 20.90 10.33 23.60 15.55 21.91 19.34 16.23 14.82
#> 153 23 79.2 58 63 29 15 13 134 24 10 113 188
#> 21.33 16.92 16.23 19.34 22.77 15.45 22.68 14.34 17.81 23.89 10.53 22.86 16.16
#> 23.1 128 171 158 157 15.1 107.1 56 190 110 77 125 133
#> 16.92 20.35 16.57 20.14 15.10 22.68 11.18 12.21 20.81 17.56 7.27 15.65 14.65
#> 70 15.2 159 92 69 181 154 93.1 45 23.2 68 125.1 107.2
#> 7.38 22.68 10.55 22.92 23.23 16.46 12.63 10.33 17.42 16.92 20.62 15.65 11.18
#> 78 157.1 86 42 183 45.1 179 140 86.1 171.1 14 40 56.1
#> 23.88 15.10 23.81 12.43 9.24 17.42 18.63 12.68 23.81 16.57 12.89 18.00 12.21
#> 110.1 171.2 125.2 55.1 40.1 145 29.1 55.2 111 117 133.1 123 168.1
#> 17.56 16.57 15.65 19.34 18.00 10.07 15.45 19.34 17.45 17.46 14.65 13.00 23.72
#> 68.1 66 56.2 55.3 187 61 197 158.1 99 57 90 23.3 106
#> 20.62 22.13 12.21 19.34 9.92 10.12 21.60 20.14 21.19 14.46 20.94 16.92 16.67
#> 181.1 130 153.1 61.1 117.1 164.2 61.2 154.1 139 63.1 68.2 155 155.1
#> 16.46 16.47 21.33 10.12 17.46 23.60 10.12 12.63 21.49 22.77 20.62 13.08 13.08
#> 57.1 156 31 28 152 132 191 118 12 131 104 163 163.1
#> 14.46 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131.1 53 12.1 84 3 48 87 178 65 138 162 148 143
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 161 162.1 3.1 120 33 102 94 38 142 94.1 163.2 162.2 160
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 146 64 65.1 31.1 83 160.1 48.1 80 48.2 71 53.1 65.2 141
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 121 148.1 65.3 185 116 122 31.2 62 141.1 82 9 28.1 82.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174 138.1 120.1 33.1 12.2 53.2 132.1 143.1 34 12.3 27 186 2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87.1 31.3 200 148.2 71.1 7 48.3 48.4 144 20
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[50]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.005769307 0.641052054 0.684162983
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.41167106 0.01250172 -0.47230793
#> grade_iii, Cure model
#> 0.48723033
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 192 16.44 1 31 1 0
#> 133 14.65 1 57 0 0
#> 159 10.55 1 50 0 1
#> 134 17.81 1 47 1 0
#> 86 23.81 1 58 0 1
#> 154 12.63 1 20 1 0
#> 85 16.44 1 36 0 0
#> 59 10.16 1 NA 1 0
#> 68 20.62 1 44 0 0
#> 106 16.67 1 49 1 0
#> 90 20.94 1 50 0 1
#> 159.1 10.55 1 50 0 1
#> 25 6.32 1 34 1 0
#> 45 17.42 1 54 0 1
#> 179 18.63 1 42 0 0
#> 181 16.46 1 45 0 1
#> 180 14.82 1 37 0 0
#> 145 10.07 1 65 1 0
#> 69 23.23 1 25 0 1
#> 107 11.18 1 54 1 0
#> 180.1 14.82 1 37 0 0
#> 136 21.83 1 43 0 1
#> 43 12.10 1 61 0 1
#> 96 14.54 1 33 0 1
#> 99 21.19 1 38 0 1
#> 52 10.42 1 52 0 1
#> 134.1 17.81 1 47 1 0
#> 106.1 16.67 1 49 1 0
#> 129 23.41 1 53 1 0
#> 183 9.24 1 67 1 0
#> 110 17.56 1 65 0 1
#> 51 18.23 1 83 0 1
#> 117 17.46 1 26 0 1
#> 199 19.81 1 NA 0 1
#> 195 11.76 1 NA 1 0
#> 88 18.37 1 47 0 0
#> 86.1 23.81 1 58 0 1
#> 130 16.47 1 53 0 1
#> 29 15.45 1 68 1 0
#> 171 16.57 1 41 0 1
#> 58 19.34 1 39 0 0
#> 113 22.86 1 34 0 0
#> 129.1 23.41 1 53 1 0
#> 77 7.27 1 67 0 1
#> 101 9.97 1 10 0 1
#> 181.1 16.46 1 45 0 1
#> 129.2 23.41 1 53 1 0
#> 139 21.49 1 63 1 0
#> 125 15.65 1 67 1 0
#> 56 12.21 1 60 0 0
#> 15 22.68 1 48 0 0
#> 199.1 19.81 1 NA 0 1
#> 171.1 16.57 1 41 0 1
#> 124 9.73 1 NA 1 0
#> 175 21.91 1 43 0 0
#> 85.1 16.44 1 36 0 0
#> 77.1 7.27 1 67 0 1
#> 57 14.46 1 45 0 1
#> 96.1 14.54 1 33 0 1
#> 168 23.72 1 70 0 0
#> 60 13.15 1 38 1 0
#> 180.2 14.82 1 37 0 0
#> 195.1 11.76 1 NA 1 0
#> 113.1 22.86 1 34 0 0
#> 101.1 9.97 1 10 0 1
#> 199.2 19.81 1 NA 0 1
#> 167 15.55 1 56 1 0
#> 24 23.89 1 38 0 0
#> 43.1 12.10 1 61 0 1
#> 179.1 18.63 1 42 0 0
#> 167.1 15.55 1 56 1 0
#> 89 11.44 1 NA 0 0
#> 58.1 19.34 1 39 0 0
#> 133.1 14.65 1 57 0 0
#> 128 20.35 1 35 0 1
#> 39 15.59 1 37 0 1
#> 70 7.38 1 30 1 0
#> 134.2 17.81 1 47 1 0
#> 134.3 17.81 1 47 1 0
#> 155 13.08 1 26 0 0
#> 158 20.14 1 74 1 0
#> 197 21.60 1 69 1 0
#> 133.2 14.65 1 57 0 0
#> 184 17.77 1 38 0 0
#> 159.2 10.55 1 50 0 1
#> 85.2 16.44 1 36 0 0
#> 78 23.88 1 43 0 0
#> 59.1 10.16 1 NA 1 0
#> 13 14.34 1 54 0 1
#> 78.1 23.88 1 43 0 0
#> 60.1 13.15 1 38 1 0
#> 145.1 10.07 1 65 1 0
#> 43.2 12.10 1 61 0 1
#> 188 16.16 1 46 0 1
#> 159.3 10.55 1 50 0 1
#> 125.1 15.65 1 67 1 0
#> 59.2 10.16 1 NA 1 0
#> 39.1 15.59 1 37 0 1
#> 100 16.07 1 60 0 0
#> 199.3 19.81 1 NA 0 1
#> 181.2 16.46 1 45 0 1
#> 110.1 17.56 1 65 0 1
#> 157 15.10 1 47 0 0
#> 58.2 19.34 1 39 0 0
#> 43.3 12.10 1 61 0 1
#> 89.1 11.44 1 NA 0 0
#> 42 12.43 1 49 0 1
#> 18 15.21 1 49 1 0
#> 113.2 22.86 1 34 0 0
#> 39.2 15.59 1 37 0 1
#> 123 13.00 1 44 1 0
#> 29.1 15.45 1 68 1 0
#> 2 24.00 0 9 0 0
#> 22 24.00 0 52 1 0
#> 28 24.00 0 67 1 0
#> 138 24.00 0 44 1 0
#> 176 24.00 0 43 0 1
#> 160 24.00 0 31 1 0
#> 73 24.00 0 NA 0 1
#> 122 24.00 0 66 0 0
#> 98 24.00 0 34 1 0
#> 73.1 24.00 0 NA 0 1
#> 160.1 24.00 0 31 1 0
#> 72 24.00 0 40 0 1
#> 198 24.00 0 66 0 1
#> 3 24.00 0 31 1 0
#> 82 24.00 0 34 0 0
#> 65 24.00 0 57 1 0
#> 27 24.00 0 63 1 0
#> 186 24.00 0 45 1 0
#> 19 24.00 0 57 0 1
#> 33 24.00 0 53 0 0
#> 47 24.00 0 38 0 1
#> 174 24.00 0 49 1 0
#> 20 24.00 0 46 1 0
#> 54 24.00 0 53 1 0
#> 191 24.00 0 60 0 1
#> 173 24.00 0 19 0 1
#> 53 24.00 0 32 0 1
#> 173.1 24.00 0 19 0 1
#> 172 24.00 0 41 0 0
#> 65.1 24.00 0 57 1 0
#> 27.1 24.00 0 63 1 0
#> 122.1 24.00 0 66 0 0
#> 156 24.00 0 50 1 0
#> 33.1 24.00 0 53 0 0
#> 87 24.00 0 27 0 0
#> 47.1 24.00 0 38 0 1
#> 165 24.00 0 47 0 0
#> 53.1 24.00 0 32 0 1
#> 146 24.00 0 63 1 0
#> 186.1 24.00 0 45 1 0
#> 82.1 24.00 0 34 0 0
#> 31 24.00 0 36 0 1
#> 131 24.00 0 66 0 0
#> 104 24.00 0 50 1 0
#> 198.1 24.00 0 66 0 1
#> 165.1 24.00 0 47 0 0
#> 148 24.00 0 61 1 0
#> 54.1 24.00 0 53 1 0
#> 144 24.00 0 28 0 1
#> 9 24.00 0 31 1 0
#> 160.2 24.00 0 31 1 0
#> 156.1 24.00 0 50 1 0
#> 186.2 24.00 0 45 1 0
#> 191.1 24.00 0 60 0 1
#> 1 24.00 0 23 1 0
#> 112 24.00 0 61 0 0
#> 11 24.00 0 42 0 1
#> 160.3 24.00 0 31 1 0
#> 80 24.00 0 41 0 0
#> 131.1 24.00 0 66 0 0
#> 138.1 24.00 0 44 1 0
#> 148.1 24.00 0 61 1 0
#> 144.1 24.00 0 28 0 1
#> 185 24.00 0 44 1 0
#> 94 24.00 0 51 0 1
#> 20.1 24.00 0 46 1 0
#> 163 24.00 0 66 0 0
#> 109 24.00 0 48 0 0
#> 156.2 24.00 0 50 1 0
#> 38 24.00 0 31 1 0
#> 9.1 24.00 0 31 1 0
#> 118 24.00 0 44 1 0
#> 165.2 24.00 0 47 0 0
#> 146.1 24.00 0 63 1 0
#> 67 24.00 0 25 0 0
#> 146.2 24.00 0 63 1 0
#> 21 24.00 0 47 0 0
#> 94.1 24.00 0 51 0 1
#> 120 24.00 0 68 0 1
#> 112.1 24.00 0 61 0 0
#> 196 24.00 0 19 0 0
#> 118.1 24.00 0 44 1 0
#> 147 24.00 0 76 1 0
#> 34 24.00 0 36 0 0
#> 182 24.00 0 35 0 0
#> 21.1 24.00 0 47 0 0
#> 31.1 24.00 0 36 0 1
#> 21.2 24.00 0 47 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.412 NA NA NA
#> 2 age, Cure model 0.0125 NA NA NA
#> 3 grade_ii, Cure model -0.472 NA NA NA
#> 4 grade_iii, Cure model 0.487 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00577 NA NA NA
#> 2 grade_ii, Survival model 0.641 NA NA NA
#> 3 grade_iii, Survival model 0.684 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.4117 0.0125 -0.4723 0.4872
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 256.8
#> Residual Deviance: 249.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.41167106 0.01250172 -0.47230793 0.48723033
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.005769307 0.641052054 0.684162983
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.543550203 0.723736074 0.887435674 0.373559191 0.056977365 0.820203888
#> [7] 0.543550203 0.263182661 0.466682050 0.251986161 0.887435674 0.992109386
#> [13] 0.456440930 0.328702971 0.515732161 0.697316031 0.928113391 0.133719883
#> [19] 0.879050280 0.697316031 0.204640984 0.845863820 0.750429282 0.240542974
#> [25] 0.919917488 0.373559191 0.466682050 0.099249242 0.960338851 0.425306758
#> [31] 0.362271566 0.446095010 0.350903249 0.056977365 0.506005078 0.661993729
#> [37] 0.486567730 0.296432711 0.145567905 0.099249242 0.976320835 0.944345835
#> [43] 0.515732161 0.099249242 0.228768410 0.599023668 0.837308038 0.179692178
#> [49] 0.486567730 0.192077479 0.543550203 0.976320835 0.768063382 0.750429282
#> [55] 0.083699039 0.785647300 0.697316031 0.145567905 0.944345835 0.644220642
#> [61] 0.007038613 0.845863820 0.328702971 0.644220642 0.296432711 0.723736074
#> [67] 0.274487036 0.617471495 0.968349519 0.373559191 0.373559191 0.802887601
#> [73] 0.285510187 0.216796894 0.723736074 0.414590397 0.887435674 0.543550203
#> [79] 0.024447630 0.776877804 0.024447630 0.785647300 0.928113391 0.845863820
#> [85] 0.580306330 0.887435674 0.599023668 0.617471495 0.589643267 0.515732161
#> [91] 0.425306758 0.688461086 0.296432711 0.845863820 0.828777760 0.679633109
#> [97] 0.145567905 0.617471495 0.811567582 0.661993729 0.000000000 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 192 133 159 134 86 154 85 68 106 90 159.1 25 45
#> 16.44 14.65 10.55 17.81 23.81 12.63 16.44 20.62 16.67 20.94 10.55 6.32 17.42
#> 179 181 180 145 69 107 180.1 136 43 96 99 52 134.1
#> 18.63 16.46 14.82 10.07 23.23 11.18 14.82 21.83 12.10 14.54 21.19 10.42 17.81
#> 106.1 129 183 110 51 117 88 86.1 130 29 171 58 113
#> 16.67 23.41 9.24 17.56 18.23 17.46 18.37 23.81 16.47 15.45 16.57 19.34 22.86
#> 129.1 77 101 181.1 129.2 139 125 56 15 171.1 175 85.1 77.1
#> 23.41 7.27 9.97 16.46 23.41 21.49 15.65 12.21 22.68 16.57 21.91 16.44 7.27
#> 57 96.1 168 60 180.2 113.1 101.1 167 24 43.1 179.1 167.1 58.1
#> 14.46 14.54 23.72 13.15 14.82 22.86 9.97 15.55 23.89 12.10 18.63 15.55 19.34
#> 133.1 128 39 70 134.2 134.3 155 158 197 133.2 184 159.2 85.2
#> 14.65 20.35 15.59 7.38 17.81 17.81 13.08 20.14 21.60 14.65 17.77 10.55 16.44
#> 78 13 78.1 60.1 145.1 43.2 188 159.3 125.1 39.1 100 181.2 110.1
#> 23.88 14.34 23.88 13.15 10.07 12.10 16.16 10.55 15.65 15.59 16.07 16.46 17.56
#> 157 58.2 43.3 42 18 113.2 39.2 123 29.1 2 22 28 138
#> 15.10 19.34 12.10 12.43 15.21 22.86 15.59 13.00 15.45 24.00 24.00 24.00 24.00
#> 176 160 122 98 160.1 72 198 3 82 65 27 186 19
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33 47 174 20 54 191 173 53 173.1 172 65.1 27.1 122.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156 33.1 87 47.1 165 53.1 146 186.1 82.1 31 131 104 198.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165.1 148 54.1 144 9 160.2 156.1 186.2 191.1 1 112 11 160.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80 131.1 138.1 148.1 144.1 185 94 20.1 163 109 156.2 38 9.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 118 165.2 146.1 67 146.2 21 94.1 120 112.1 196 118.1 147 34
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 182 21.1 31.1 21.2
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[51]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.00916194 1.09113578 0.59909547
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.448559140 0.007633766 -0.156294229
#> grade_iii, Cure model
#> 1.043641921
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 164 23.60 1 76 0 1
#> 85 16.44 1 36 0 0
#> 169 22.41 1 46 0 0
#> 37 12.52 1 57 1 0
#> 14 12.89 1 21 0 0
#> 175 21.91 1 43 0 0
#> 195 11.76 1 NA 1 0
#> 92 22.92 1 47 0 1
#> 189 10.51 1 NA 1 0
#> 61 10.12 1 36 0 1
#> 13 14.34 1 54 0 1
#> 166 19.98 1 48 0 0
#> 169.1 22.41 1 46 0 0
#> 97 19.14 1 65 0 1
#> 32 20.90 1 37 1 0
#> 106 16.67 1 49 1 0
#> 86 23.81 1 58 0 1
#> 91 5.33 1 61 0 1
#> 177 12.53 1 75 0 0
#> 89 11.44 1 NA 0 0
#> 70 7.38 1 30 1 0
#> 70.1 7.38 1 30 1 0
#> 105 19.75 1 60 0 0
#> 69 23.23 1 25 0 1
#> 39 15.59 1 37 0 1
#> 101 9.97 1 10 0 1
#> 177.1 12.53 1 75 0 0
#> 78 23.88 1 43 0 0
#> 16 8.71 1 71 0 1
#> 45 17.42 1 54 0 1
#> 134 17.81 1 47 1 0
#> 18 15.21 1 49 1 0
#> 61.1 10.12 1 36 0 1
#> 171 16.57 1 41 0 1
#> 58 19.34 1 39 0 0
#> 85.1 16.44 1 36 0 0
#> 8 18.43 1 32 0 0
#> 30 17.43 1 78 0 0
#> 86.1 23.81 1 58 0 1
#> 157 15.10 1 47 0 0
#> 49 12.19 1 48 1 0
#> 136 21.83 1 43 0 1
#> 139 21.49 1 63 1 0
#> 169.2 22.41 1 46 0 0
#> 51 18.23 1 83 0 1
#> 4 17.64 1 NA 0 1
#> 5 16.43 1 51 0 1
#> 107 11.18 1 54 1 0
#> 129 23.41 1 53 1 0
#> 105.1 19.75 1 60 0 0
#> 59 10.16 1 NA 1 0
#> 130 16.47 1 53 0 1
#> 168 23.72 1 70 0 0
#> 194 22.40 1 38 0 1
#> 154 12.63 1 20 1 0
#> 43 12.10 1 61 0 1
#> 6 15.64 1 39 0 0
#> 105.2 19.75 1 60 0 0
#> 61.2 10.12 1 36 0 1
#> 123 13.00 1 44 1 0
#> 113 22.86 1 34 0 0
#> 92.1 22.92 1 47 0 1
#> 93 10.33 1 52 0 1
#> 37.1 12.52 1 57 1 0
#> 91.1 5.33 1 61 0 1
#> 101.1 9.97 1 10 0 1
#> 166.1 19.98 1 48 0 0
#> 51.1 18.23 1 83 0 1
#> 32.1 20.90 1 37 1 0
#> 199 19.81 1 NA 0 1
#> 159 10.55 1 50 0 1
#> 158 20.14 1 74 1 0
#> 55 19.34 1 69 0 1
#> 108 18.29 1 39 0 1
#> 15 22.68 1 48 0 0
#> 117 17.46 1 26 0 1
#> 70.2 7.38 1 30 1 0
#> 16.1 8.71 1 71 0 1
#> 145 10.07 1 65 1 0
#> 99 21.19 1 38 0 1
#> 24 23.89 1 38 0 0
#> 24.1 23.89 1 38 0 0
#> 170 19.54 1 43 0 1
#> 24.2 23.89 1 38 0 0
#> 52 10.42 1 52 0 1
#> 187 9.92 1 39 1 0
#> 125 15.65 1 67 1 0
#> 81 14.06 1 34 0 0
#> 45.1 17.42 1 54 0 1
#> 24.3 23.89 1 38 0 0
#> 107.1 11.18 1 54 1 0
#> 195.1 11.76 1 NA 1 0
#> 36 21.19 1 48 0 1
#> 105.3 19.75 1 60 0 0
#> 37.2 12.52 1 57 1 0
#> 187.1 9.92 1 39 1 0
#> 8.1 18.43 1 32 0 0
#> 58.1 19.34 1 39 0 0
#> 175.1 21.91 1 43 0 0
#> 4.1 17.64 1 NA 0 1
#> 92.2 22.92 1 47 0 1
#> 106.1 16.67 1 49 1 0
#> 114 13.68 1 NA 0 0
#> 57 14.46 1 45 0 1
#> 164.1 23.60 1 76 0 1
#> 10 10.53 1 34 0 0
#> 188 16.16 1 46 0 1
#> 81.1 14.06 1 34 0 0
#> 170.1 19.54 1 43 0 1
#> 23 16.92 1 61 0 0
#> 159.1 10.55 1 50 0 1
#> 101.2 9.97 1 10 0 1
#> 141 24.00 0 44 1 0
#> 9 24.00 0 31 1 0
#> 44 24.00 0 56 0 0
#> 102 24.00 0 49 0 0
#> 3 24.00 0 31 1 0
#> 19 24.00 0 57 0 1
#> 176 24.00 0 43 0 1
#> 47 24.00 0 38 0 1
#> 173 24.00 0 19 0 1
#> 35 24.00 0 51 0 0
#> 126 24.00 0 48 0 0
#> 160 24.00 0 31 1 0
#> 74 24.00 0 43 0 1
#> 62 24.00 0 71 0 0
#> 73 24.00 0 NA 0 1
#> 200 24.00 0 64 0 0
#> 38 24.00 0 31 1 0
#> 109 24.00 0 48 0 0
#> 22 24.00 0 52 1 0
#> 193 24.00 0 45 0 1
#> 20 24.00 0 46 1 0
#> 142 24.00 0 53 0 0
#> 80 24.00 0 41 0 0
#> 75 24.00 0 21 1 0
#> 1 24.00 0 23 1 0
#> 119 24.00 0 17 0 0
#> 135 24.00 0 58 1 0
#> 46 24.00 0 71 0 0
#> 193.1 24.00 0 45 0 1
#> 62.1 24.00 0 71 0 0
#> 174 24.00 0 49 1 0
#> 173.1 24.00 0 19 0 1
#> 172 24.00 0 41 0 0
#> 131 24.00 0 66 0 0
#> 118 24.00 0 44 1 0
#> 53 24.00 0 32 0 1
#> 98 24.00 0 34 1 0
#> 163 24.00 0 66 0 0
#> 48 24.00 0 31 1 0
#> 116 24.00 0 58 0 1
#> 87 24.00 0 27 0 0
#> 2 24.00 0 9 0 0
#> 53.1 24.00 0 32 0 1
#> 80.1 24.00 0 41 0 0
#> 109.1 24.00 0 48 0 0
#> 54 24.00 0 53 1 0
#> 19.1 24.00 0 57 0 1
#> 74.1 24.00 0 43 0 1
#> 1.1 24.00 0 23 1 0
#> 71 24.00 0 51 0 0
#> 131.1 24.00 0 66 0 0
#> 21 24.00 0 47 0 0
#> 185 24.00 0 44 1 0
#> 74.2 24.00 0 43 0 1
#> 121 24.00 0 57 1 0
#> 20.1 24.00 0 46 1 0
#> 122 24.00 0 66 0 0
#> 196 24.00 0 19 0 0
#> 54.1 24.00 0 53 1 0
#> 163.1 24.00 0 66 0 0
#> 122.1 24.00 0 66 0 0
#> 48.1 24.00 0 31 1 0
#> 2.1 24.00 0 9 0 0
#> 148 24.00 0 61 1 0
#> 80.2 24.00 0 41 0 0
#> 80.3 24.00 0 41 0 0
#> 135.1 24.00 0 58 1 0
#> 87.1 24.00 0 27 0 0
#> 198 24.00 0 66 0 1
#> 62.2 24.00 0 71 0 0
#> 151 24.00 0 42 0 0
#> 160.1 24.00 0 31 1 0
#> 146 24.00 0 63 1 0
#> 48.2 24.00 0 31 1 0
#> 104 24.00 0 50 1 0
#> 84 24.00 0 39 0 1
#> 142.1 24.00 0 53 0 0
#> 44.1 24.00 0 56 0 0
#> 17 24.00 0 38 0 1
#> 46.1 24.00 0 71 0 0
#> 147 24.00 0 76 1 0
#> 131.2 24.00 0 66 0 0
#> 28 24.00 0 67 1 0
#> 73.1 24.00 0 NA 0 1
#> 20.2 24.00 0 46 1 0
#> 151.1 24.00 0 42 0 0
#> 64 24.00 0 43 0 0
#> 138 24.00 0 44 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.449 NA NA NA
#> 2 age, Cure model 0.00763 NA NA NA
#> 3 grade_ii, Cure model -0.156 NA NA NA
#> 4 grade_iii, Cure model 1.04 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00916 NA NA NA
#> 2 grade_ii, Survival model 1.09 NA NA NA
#> 3 grade_iii, Survival model 0.599 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.448559 0.007634 -0.156294 1.043642
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.5
#> Residual Deviance: 248 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.448559140 0.007633766 -0.156294229 1.043641921
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.00916194 1.09113578 0.59909547
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.081031039 0.581393342 0.175015119 0.755845379 0.717812875 0.217359776
#> [7] 0.125988913 0.864431470 0.679249797 0.310766552 0.175015119 0.419508759
#> [13] 0.281993386 0.542080442 0.048323527 0.983646908 0.736861708 0.959202908
#> [19] 0.959202908 0.330068993 0.115282142 0.640457875 0.899657564 0.736861708
#> [25] 0.036309111 0.942290667 0.511725573 0.481234165 0.650236240 0.864431470
#> [31] 0.561703343 0.389428300 0.581393342 0.429784374 0.501522158 0.048323527
#> [37] 0.659883940 0.783352403 0.239309563 0.250429573 0.175015119 0.460667813
#> [43] 0.601082205 0.801705358 0.104111941 0.330068993 0.571558532 0.068897983
#> [49] 0.206461644 0.727429507 0.792531060 0.630634961 0.330068993 0.864431470
#> [55] 0.708218741 0.154277818 0.125988913 0.855456262 0.755845379 0.983646908
#> [61] 0.899657564 0.310766552 0.460667813 0.281993386 0.819616589 0.301176152
#> [67] 0.389428300 0.450336812 0.164530162 0.491423656 0.959202908 0.942290667
#> [73] 0.890827152 0.261227576 0.008807633 0.008807633 0.369438286 0.008807633
#> [79] 0.846468749 0.925393629 0.620857806 0.688903235 0.511725573 0.008807633
#> [85] 0.801705358 0.261227576 0.330068993 0.755845379 0.925393629 0.429784374
#> [91] 0.389428300 0.217359776 0.125988913 0.542080442 0.669581247 0.081031039
#> [97] 0.837468764 0.610985557 0.688903235 0.369438286 0.531841715 0.819616589
#> [103] 0.899657564 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 164 85 169 37 14 175 92 61 13 166 169.1 97 32
#> 23.60 16.44 22.41 12.52 12.89 21.91 22.92 10.12 14.34 19.98 22.41 19.14 20.90
#> 106 86 91 177 70 70.1 105 69 39 101 177.1 78 16
#> 16.67 23.81 5.33 12.53 7.38 7.38 19.75 23.23 15.59 9.97 12.53 23.88 8.71
#> 45 134 18 61.1 171 58 85.1 8 30 86.1 157 49 136
#> 17.42 17.81 15.21 10.12 16.57 19.34 16.44 18.43 17.43 23.81 15.10 12.19 21.83
#> 139 169.2 51 5 107 129 105.1 130 168 194 154 43 6
#> 21.49 22.41 18.23 16.43 11.18 23.41 19.75 16.47 23.72 22.40 12.63 12.10 15.64
#> 105.2 61.2 123 113 92.1 93 37.1 91.1 101.1 166.1 51.1 32.1 159
#> 19.75 10.12 13.00 22.86 22.92 10.33 12.52 5.33 9.97 19.98 18.23 20.90 10.55
#> 158 55 108 15 117 70.2 16.1 145 99 24 24.1 170 24.2
#> 20.14 19.34 18.29 22.68 17.46 7.38 8.71 10.07 21.19 23.89 23.89 19.54 23.89
#> 52 187 125 81 45.1 24.3 107.1 36 105.3 37.2 187.1 8.1 58.1
#> 10.42 9.92 15.65 14.06 17.42 23.89 11.18 21.19 19.75 12.52 9.92 18.43 19.34
#> 175.1 92.2 106.1 57 164.1 10 188 81.1 170.1 23 159.1 101.2 141
#> 21.91 22.92 16.67 14.46 23.60 10.53 16.16 14.06 19.54 16.92 10.55 9.97 24.00
#> 9 44 102 3 19 176 47 173 35 126 160 74 62
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 200 38 109 22 193 20 142 80 75 1 119 135 46
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193.1 62.1 174 173.1 172 131 118 53 98 163 48 116 87
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 2 53.1 80.1 109.1 54 19.1 74.1 1.1 71 131.1 21 185 74.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 121 20.1 122 196 54.1 163.1 122.1 48.1 2.1 148 80.2 80.3 135.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87.1 198 62.2 151 160.1 146 48.2 104 84 142.1 44.1 17 46.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 147 131.2 28 20.2 151.1 64 138
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[52]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.008085326 0.273451104 0.333350481
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.90825647 0.02228347 0.03147412
#> grade_iii, Cure model
#> 0.26638258
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 101 9.97 1 10 0 1
#> 107 11.18 1 54 1 0
#> 170 19.54 1 43 0 1
#> 61 10.12 1 36 0 1
#> 100 16.07 1 60 0 0
#> 8 18.43 1 32 0 0
#> 169 22.41 1 46 0 0
#> 77 7.27 1 67 0 1
#> 81 14.06 1 34 0 0
#> 149 8.37 1 33 1 0
#> 166 19.98 1 48 0 0
#> 192 16.44 1 31 1 0
#> 63 22.77 1 31 1 0
#> 50 10.02 1 NA 1 0
#> 99 21.19 1 38 0 1
#> 30 17.43 1 78 0 0
#> 96 14.54 1 33 0 1
#> 149.1 8.37 1 33 1 0
#> 36 21.19 1 48 0 1
#> 63.1 22.77 1 31 1 0
#> 130 16.47 1 53 0 1
#> 145 10.07 1 65 1 0
#> 140 12.68 1 59 1 0
#> 159 10.55 1 50 0 1
#> 177 12.53 1 75 0 0
#> 168 23.72 1 70 0 0
#> 40 18.00 1 28 1 0
#> 124 9.73 1 NA 1 0
#> 180 14.82 1 37 0 0
#> 180.1 14.82 1 37 0 0
#> 155 13.08 1 26 0 0
#> 86 23.81 1 58 0 1
#> 56 12.21 1 60 0 0
#> 183 9.24 1 67 1 0
#> 158 20.14 1 74 1 0
#> 6 15.64 1 39 0 0
#> 39 15.59 1 37 0 1
#> 113 22.86 1 34 0 0
#> 14 12.89 1 21 0 0
#> 70 7.38 1 30 1 0
#> 184 17.77 1 38 0 0
#> 4 17.64 1 NA 0 1
#> 153 21.33 1 55 1 0
#> 36.1 21.19 1 48 0 1
#> 106 16.67 1 49 1 0
#> 4.1 17.64 1 NA 0 1
#> 114 13.68 1 NA 0 0
#> 177.1 12.53 1 75 0 0
#> 13 14.34 1 54 0 1
#> 70.1 7.38 1 30 1 0
#> 91 5.33 1 61 0 1
#> 23 16.92 1 61 0 0
#> 139 21.49 1 63 1 0
#> 190 20.81 1 42 1 0
#> 63.2 22.77 1 31 1 0
#> 90 20.94 1 50 0 1
#> 179 18.63 1 42 0 0
#> 40.1 18.00 1 28 1 0
#> 68 20.62 1 44 0 0
#> 192.1 16.44 1 31 1 0
#> 16 8.71 1 71 0 1
#> 114.1 13.68 1 NA 0 0
#> 15 22.68 1 48 0 0
#> 187 9.92 1 39 1 0
#> 93 10.33 1 52 0 1
#> 55 19.34 1 69 0 1
#> 194 22.40 1 38 0 1
#> 169.1 22.41 1 46 0 0
#> 89 11.44 1 NA 0 0
#> 4.2 17.64 1 NA 0 1
#> 63.3 22.77 1 31 1 0
#> 197 21.60 1 69 1 0
#> 61.1 10.12 1 36 0 1
#> 149.2 8.37 1 33 1 0
#> 41 18.02 1 40 1 0
#> 58 19.34 1 39 0 0
#> 179.1 18.63 1 42 0 0
#> 77.1 7.27 1 67 0 1
#> 91.1 5.33 1 61 0 1
#> 59 10.16 1 NA 1 0
#> 166.1 19.98 1 48 0 0
#> 125 15.65 1 67 1 0
#> 60 13.15 1 38 1 0
#> 139.1 21.49 1 63 1 0
#> 77.2 7.27 1 67 0 1
#> 180.2 14.82 1 37 0 0
#> 150 20.33 1 48 0 0
#> 166.2 19.98 1 48 0 0
#> 125.1 15.65 1 67 1 0
#> 30.1 17.43 1 78 0 0
#> 88 18.37 1 47 0 0
#> 78 23.88 1 43 0 0
#> 91.2 5.33 1 61 0 1
#> 56.1 12.21 1 60 0 0
#> 180.3 14.82 1 37 0 0
#> 127 3.53 1 62 0 1
#> 37 12.52 1 57 1 0
#> 92 22.92 1 47 0 1
#> 130.1 16.47 1 53 0 1
#> 117 17.46 1 26 0 1
#> 37.1 12.52 1 57 1 0
#> 93.1 10.33 1 52 0 1
#> 36.2 21.19 1 48 0 1
#> 90.1 20.94 1 50 0 1
#> 184.1 17.77 1 38 0 0
#> 159.1 10.55 1 50 0 1
#> 106.1 16.67 1 49 1 0
#> 183.1 9.24 1 67 1 0
#> 153.1 21.33 1 55 1 0
#> 113.1 22.86 1 34 0 0
#> 76 19.22 1 54 0 1
#> 194.1 22.40 1 38 0 1
#> 120 24.00 0 68 0 1
#> 67 24.00 0 25 0 0
#> 191 24.00 0 60 0 1
#> 119 24.00 0 17 0 0
#> 144 24.00 0 28 0 1
#> 75 24.00 0 21 1 0
#> 35 24.00 0 51 0 0
#> 72 24.00 0 40 0 1
#> 72.1 24.00 0 40 0 1
#> 87 24.00 0 27 0 0
#> 28 24.00 0 67 1 0
#> 182 24.00 0 35 0 0
#> 119.1 24.00 0 17 0 0
#> 2 24.00 0 9 0 0
#> 17 24.00 0 38 0 1
#> 83 24.00 0 6 0 0
#> 73 24.00 0 NA 0 1
#> 132 24.00 0 55 0 0
#> 1 24.00 0 23 1 0
#> 115 24.00 0 NA 1 0
#> 141 24.00 0 44 1 0
#> 152 24.00 0 36 0 1
#> 138 24.00 0 44 1 0
#> 80 24.00 0 41 0 0
#> 80.1 24.00 0 41 0 0
#> 47 24.00 0 38 0 1
#> 144.1 24.00 0 28 0 1
#> 102 24.00 0 49 0 0
#> 54 24.00 0 53 1 0
#> 27 24.00 0 63 1 0
#> 95 24.00 0 68 0 1
#> 200 24.00 0 64 0 0
#> 75.1 24.00 0 21 1 0
#> 137 24.00 0 45 1 0
#> 48 24.00 0 31 1 0
#> 9 24.00 0 31 1 0
#> 47.1 24.00 0 38 0 1
#> 132.1 24.00 0 55 0 0
#> 33 24.00 0 53 0 0
#> 185 24.00 0 44 1 0
#> 119.2 24.00 0 17 0 0
#> 48.1 24.00 0 31 1 0
#> 151 24.00 0 42 0 0
#> 20 24.00 0 46 1 0
#> 22 24.00 0 52 1 0
#> 48.2 24.00 0 31 1 0
#> 95.1 24.00 0 68 0 1
#> 72.2 24.00 0 40 0 1
#> 67.1 24.00 0 25 0 0
#> 182.1 24.00 0 35 0 0
#> 156 24.00 0 50 1 0
#> 22.1 24.00 0 52 1 0
#> 142 24.00 0 53 0 0
#> 132.2 24.00 0 55 0 0
#> 3 24.00 0 31 1 0
#> 151.1 24.00 0 42 0 0
#> 198 24.00 0 66 0 1
#> 148 24.00 0 61 1 0
#> 31 24.00 0 36 0 1
#> 196 24.00 0 19 0 0
#> 53 24.00 0 32 0 1
#> 160 24.00 0 31 1 0
#> 119.3 24.00 0 17 0 0
#> 46 24.00 0 71 0 0
#> 141.1 24.00 0 44 1 0
#> 198.1 24.00 0 66 0 1
#> 132.3 24.00 0 55 0 0
#> 172 24.00 0 41 0 0
#> 109 24.00 0 48 0 0
#> 132.4 24.00 0 55 0 0
#> 120.1 24.00 0 68 0 1
#> 20.1 24.00 0 46 1 0
#> 65 24.00 0 57 1 0
#> 98 24.00 0 34 1 0
#> 12 24.00 0 63 0 0
#> 182.2 24.00 0 35 0 0
#> 73.1 24.00 0 NA 0 1
#> 135 24.00 0 58 1 0
#> 22.2 24.00 0 52 1 0
#> 7 24.00 0 37 1 0
#> 98.1 24.00 0 34 1 0
#> 53.1 24.00 0 32 0 1
#> 165 24.00 0 47 0 0
#> 19 24.00 0 57 0 1
#> 151.2 24.00 0 42 0 0
#> 116 24.00 0 58 0 1
#> 121 24.00 0 57 1 0
#> 17.1 24.00 0 38 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.908 NA NA NA
#> 2 age, Cure model 0.0223 NA NA NA
#> 3 grade_ii, Cure model 0.0315 NA NA NA
#> 4 grade_iii, Cure model 0.266 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00809 NA NA NA
#> 2 grade_ii, Survival model 0.273 NA NA NA
#> 3 grade_iii, Survival model 0.333 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.90826 0.02228 0.03147 0.26638
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 258.9
#> Residual Deviance: 252.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.90825647 0.02228347 0.03147412 0.26638258
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.008085326 0.273451104 0.333350481
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.90594639 0.85796232 0.53327591 0.88824767 0.71306872 0.58353803
#> [7] 0.29568948 0.96261626 0.78751333 0.93476985 0.50709460 0.69889617
#> [13] 0.22077092 0.41126037 0.64708211 0.77420061 0.93476985 0.41126037
#> [19] 0.22077092 0.68452284 0.90006539 0.81377297 0.86414999 0.82025525
#> [25] 0.13157212 0.60795125 0.74760182 0.74760182 0.80068211 0.10001440
#> [31] 0.84553929 0.91763928 0.49798601 0.73389362 0.74077570 0.18104345
#> [37] 0.80723245 0.95151084 0.62369691 0.38890296 0.41126037 0.66979630
#> [43] 0.82025525 0.78088987 0.95151084 0.97883475 0.66223267 0.36510927
#> [49] 0.46969576 0.22077092 0.45053974 0.56718121 0.60795125 0.47920767
#> [55] 0.69889617 0.92908246 0.27997442 0.91180787 0.87629201 0.54200806
#> [61] 0.32492531 0.29568948 0.22077092 0.35197907 0.88824767 0.93476985
#> [67] 0.59989052 0.54200806 0.56718121 0.96261626 0.97883475 0.50709460
#> [73] 0.72014643 0.79411921 0.36510927 0.96261626 0.74760182 0.48863961
#> [79] 0.50709460 0.72014643 0.64708211 0.59174039 0.04935216 0.97883475
#> [85] 0.84553929 0.74760182 0.99471502 0.83300125 0.15829819 0.68452284
#> [91] 0.63930091 0.83300125 0.87629201 0.41126037 0.45053974 0.62369691
#> [97] 0.86414999 0.66979630 0.91763928 0.38890296 0.18104345 0.55884506
#> [103] 0.32492531 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000
#>
#> $Time
#> 101 107 170 61 100 8 169 77 81 149 166 192 63
#> 9.97 11.18 19.54 10.12 16.07 18.43 22.41 7.27 14.06 8.37 19.98 16.44 22.77
#> 99 30 96 149.1 36 63.1 130 145 140 159 177 168 40
#> 21.19 17.43 14.54 8.37 21.19 22.77 16.47 10.07 12.68 10.55 12.53 23.72 18.00
#> 180 180.1 155 86 56 183 158 6 39 113 14 70 184
#> 14.82 14.82 13.08 23.81 12.21 9.24 20.14 15.64 15.59 22.86 12.89 7.38 17.77
#> 153 36.1 106 177.1 13 70.1 91 23 139 190 63.2 90 179
#> 21.33 21.19 16.67 12.53 14.34 7.38 5.33 16.92 21.49 20.81 22.77 20.94 18.63
#> 40.1 68 192.1 16 15 187 93 55 194 169.1 63.3 197 61.1
#> 18.00 20.62 16.44 8.71 22.68 9.92 10.33 19.34 22.40 22.41 22.77 21.60 10.12
#> 149.2 41 58 179.1 77.1 91.1 166.1 125 60 139.1 77.2 180.2 150
#> 8.37 18.02 19.34 18.63 7.27 5.33 19.98 15.65 13.15 21.49 7.27 14.82 20.33
#> 166.2 125.1 30.1 88 78 91.2 56.1 180.3 127 37 92 130.1 117
#> 19.98 15.65 17.43 18.37 23.88 5.33 12.21 14.82 3.53 12.52 22.92 16.47 17.46
#> 37.1 93.1 36.2 90.1 184.1 159.1 106.1 183.1 153.1 113.1 76 194.1 120
#> 12.52 10.33 21.19 20.94 17.77 10.55 16.67 9.24 21.33 22.86 19.22 22.40 24.00
#> 67 191 119 144 75 35 72 72.1 87 28 182 119.1 2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 17 83 132 1 141 152 138 80 80.1 47 144.1 102 54
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 27 95 200 75.1 137 48 9 47.1 132.1 33 185 119.2 48.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 151 20 22 48.2 95.1 72.2 67.1 182.1 156 22.1 142 132.2 3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 151.1 198 148 31 196 53 160 119.3 46 141.1 198.1 132.3 172
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 109 132.4 120.1 20.1 65 98 12 182.2 135 22.2 7 98.1 53.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165 19 151.2 116 121 17.1
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[53]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.01493714 -0.06975825 0.13855571
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.9089413 0.0144930 0.2446462
#> grade_iii, Cure model
#> 0.9219518
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 63 22.77 1 31 1 0
#> 136 21.83 1 43 0 1
#> 197 21.60 1 69 1 0
#> 169 22.41 1 46 0 0
#> 6 15.64 1 39 0 0
#> 57 14.46 1 45 0 1
#> 129 23.41 1 53 1 0
#> 92 22.92 1 47 0 1
#> 5 16.43 1 51 0 1
#> 97 19.14 1 65 0 1
#> 92.1 22.92 1 47 0 1
#> 158 20.14 1 74 1 0
#> 5.1 16.43 1 51 0 1
#> 51 18.23 1 83 0 1
#> 199 19.81 1 NA 0 1
#> 77 7.27 1 67 0 1
#> 170 19.54 1 43 0 1
#> 159 10.55 1 50 0 1
#> 183 9.24 1 67 1 0
#> 127 3.53 1 62 0 1
#> 56 12.21 1 60 0 0
#> 51.1 18.23 1 83 0 1
#> 57.1 14.46 1 45 0 1
#> 78 23.88 1 43 0 0
#> 97.1 19.14 1 65 0 1
#> 77.1 7.27 1 67 0 1
#> 76 19.22 1 54 0 1
#> 124 9.73 1 NA 1 0
#> 50 10.02 1 NA 1 0
#> 63.1 22.77 1 31 1 0
#> 36 21.19 1 48 0 1
#> 18 15.21 1 49 1 0
#> 14 12.89 1 21 0 0
#> 90 20.94 1 50 0 1
#> 110 17.56 1 65 0 1
#> 85 16.44 1 36 0 0
#> 78.1 23.88 1 43 0 0
#> 8 18.43 1 32 0 0
#> 187 9.92 1 39 1 0
#> 167 15.55 1 56 1 0
#> 133 14.65 1 57 0 0
#> 128 20.35 1 35 0 1
#> 145 10.07 1 65 1 0
#> 99 21.19 1 38 0 1
#> 170.1 19.54 1 43 0 1
#> 192 16.44 1 31 1 0
#> 23 16.92 1 61 0 0
#> 136.1 21.83 1 43 0 1
#> 63.2 22.77 1 31 1 0
#> 128.1 20.35 1 35 0 1
#> 63.3 22.77 1 31 1 0
#> 110.1 17.56 1 65 0 1
#> 134 17.81 1 47 1 0
#> 130 16.47 1 53 0 1
#> 136.2 21.83 1 43 0 1
#> 150 20.33 1 48 0 0
#> 8.1 18.43 1 32 0 0
#> 190 20.81 1 42 1 0
#> 130.1 16.47 1 53 0 1
#> 153 21.33 1 55 1 0
#> 197.1 21.60 1 69 1 0
#> 50.1 10.02 1 NA 1 0
#> 29 15.45 1 68 1 0
#> 170.2 19.54 1 43 0 1
#> 39 15.59 1 37 0 1
#> 139 21.49 1 63 1 0
#> 15 22.68 1 48 0 0
#> 6.1 15.64 1 39 0 0
#> 167.1 15.55 1 56 1 0
#> 159.1 10.55 1 50 0 1
#> 59 10.16 1 NA 1 0
#> 40 18.00 1 28 1 0
#> 77.2 7.27 1 67 0 1
#> 32 20.90 1 37 1 0
#> 179 18.63 1 42 0 0
#> 50.2 10.02 1 NA 1 0
#> 105 19.75 1 60 0 0
#> 157 15.10 1 47 0 0
#> 32.1 20.90 1 37 1 0
#> 169.1 22.41 1 46 0 0
#> 187.1 9.92 1 39 1 0
#> 41 18.02 1 40 1 0
#> 8.2 18.43 1 32 0 0
#> 16 8.71 1 71 0 1
#> 77.3 7.27 1 67 0 1
#> 167.2 15.55 1 56 1 0
#> 197.2 21.60 1 69 1 0
#> 13 14.34 1 54 0 1
#> 139.1 21.49 1 63 1 0
#> 181 16.46 1 45 0 1
#> 26 15.77 1 49 0 1
#> 85.1 16.44 1 36 0 0
#> 133.1 14.65 1 57 0 0
#> 50.3 10.02 1 NA 1 0
#> 92.2 22.92 1 47 0 1
#> 50.4 10.02 1 NA 1 0
#> 114 13.68 1 NA 0 0
#> 101 9.97 1 10 0 1
#> 88 18.37 1 47 0 0
#> 5.2 16.43 1 51 0 1
#> 195 11.76 1 NA 1 0
#> 40.1 18.00 1 28 1 0
#> 8.3 18.43 1 32 0 0
#> 149 8.37 1 33 1 0
#> 92.3 22.92 1 47 0 1
#> 99.1 21.19 1 38 0 1
#> 124.1 9.73 1 NA 1 0
#> 179.1 18.63 1 42 0 0
#> 93 10.33 1 52 0 1
#> 128.2 20.35 1 35 0 1
#> 158.1 20.14 1 74 1 0
#> 183.1 9.24 1 67 1 0
#> 151 24.00 0 42 0 0
#> 17 24.00 0 38 0 1
#> 94 24.00 0 51 0 1
#> 193 24.00 0 45 0 1
#> 173 24.00 0 19 0 1
#> 115 24.00 0 NA 1 0
#> 98 24.00 0 34 1 0
#> 74 24.00 0 43 0 1
#> 109 24.00 0 48 0 0
#> 83 24.00 0 6 0 0
#> 138 24.00 0 44 1 0
#> 65 24.00 0 57 1 0
#> 72 24.00 0 40 0 1
#> 109.1 24.00 0 48 0 0
#> 200 24.00 0 64 0 0
#> 72.1 24.00 0 40 0 1
#> 165 24.00 0 47 0 0
#> 135 24.00 0 58 1 0
#> 122 24.00 0 66 0 0
#> 121 24.00 0 57 1 0
#> 84 24.00 0 39 0 1
#> 131 24.00 0 66 0 0
#> 38 24.00 0 31 1 0
#> 84.1 24.00 0 39 0 1
#> 27 24.00 0 63 1 0
#> 126 24.00 0 48 0 0
#> 173.1 24.00 0 19 0 1
#> 103 24.00 0 56 1 0
#> 109.2 24.00 0 48 0 0
#> 95 24.00 0 68 0 1
#> 87 24.00 0 27 0 0
#> 28 24.00 0 67 1 0
#> 82 24.00 0 34 0 0
#> 119 24.00 0 17 0 0
#> 12 24.00 0 63 0 0
#> 112 24.00 0 61 0 0
#> 148 24.00 0 61 1 0
#> 200.1 24.00 0 64 0 0
#> 83.1 24.00 0 6 0 0
#> 72.2 24.00 0 40 0 1
#> 103.1 24.00 0 56 1 0
#> 120 24.00 0 68 0 1
#> 118 24.00 0 44 1 0
#> 22 24.00 0 52 1 0
#> 152 24.00 0 36 0 1
#> 34 24.00 0 36 0 0
#> 65.1 24.00 0 57 1 0
#> 53 24.00 0 32 0 1
#> 131.1 24.00 0 66 0 0
#> 9 24.00 0 31 1 0
#> 191 24.00 0 60 0 1
#> 48 24.00 0 31 1 0
#> 98.1 24.00 0 34 1 0
#> 135.1 24.00 0 58 1 0
#> 151.1 24.00 0 42 0 0
#> 198 24.00 0 66 0 1
#> 75 24.00 0 21 1 0
#> 176 24.00 0 43 0 1
#> 165.1 24.00 0 47 0 0
#> 121.1 24.00 0 57 1 0
#> 141 24.00 0 44 1 0
#> 162 24.00 0 51 0 0
#> 126.1 24.00 0 48 0 0
#> 20 24.00 0 46 1 0
#> 75.1 24.00 0 21 1 0
#> 115.1 24.00 0 NA 1 0
#> 162.1 24.00 0 51 0 0
#> 182 24.00 0 35 0 0
#> 72.3 24.00 0 40 0 1
#> 28.1 24.00 0 67 1 0
#> 98.2 24.00 0 34 1 0
#> 191.1 24.00 0 60 0 1
#> 46 24.00 0 71 0 0
#> 122.1 24.00 0 66 0 0
#> 185 24.00 0 44 1 0
#> 135.2 24.00 0 58 1 0
#> 94.1 24.00 0 51 0 1
#> 72.4 24.00 0 40 0 1
#> 65.2 24.00 0 57 1 0
#> 196 24.00 0 19 0 0
#> 115.2 24.00 0 NA 1 0
#> 102 24.00 0 49 0 0
#> 115.3 24.00 0 NA 1 0
#> 7 24.00 0 37 1 0
#> 126.2 24.00 0 48 0 0
#> 34.1 24.00 0 36 0 0
#> 160 24.00 0 31 1 0
#> 75.2 24.00 0 21 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.909 NA NA NA
#> 2 age, Cure model 0.0145 NA NA NA
#> 3 grade_ii, Cure model 0.245 NA NA NA
#> 4 grade_iii, Cure model 0.922 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0149 NA NA NA
#> 2 grade_ii, Survival model -0.0698 NA NA NA
#> 3 grade_iii, Survival model 0.139 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.90894 0.01449 0.24465 0.92195
#>
#> Degrees of Freedom: 184 Total (i.e. Null); 181 Residual
#> Null Deviance: 254.9
#> Residual Deviance: 245.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.9089413 0.0144930 0.2446462 0.9219518
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.01493714 -0.06975825 0.13855571
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.2989707 0.4064326 0.4443520 0.3774998 0.8411433 0.8997361 0.1935125
#> [8] 0.2295197 0.8188090 0.6643230 0.2295197 0.6095136 0.8188090 0.7269926
#> [15] 0.9777344 0.6338954 0.9249743 0.9589464 0.9955532 0.9199767 0.7269926
#> [22] 0.8997361 0.1143495 0.6643230 0.9777344 0.6567533 0.2989707 0.5092100
#> [29] 0.8789087 0.9149393 0.5378740 0.7654877 0.8015311 0.1143495 0.6928422
#> [36] 0.9493600 0.8576168 0.8894352 0.5749436 0.9396753 0.5092100 0.6338954
#> [43] 0.8015311 0.7777398 0.4064326 0.2989707 0.5749436 0.2989707 0.7654877
#> [50] 0.7591292 0.7838187 0.4064326 0.6008746 0.6928422 0.5657729 0.7838187
#> [57] 0.4987919 0.4443520 0.8735996 0.6338954 0.8521372 0.4776843 0.3615111
#> [64] 0.8411433 0.8576168 0.9249743 0.7463717 0.9777344 0.5473593 0.6787133
#> [71] 0.6258345 0.8841879 0.5473593 0.3774998 0.9493600 0.7399192 0.6928422
#> [78] 0.9683878 0.9777344 0.8576168 0.4443520 0.9098917 0.4776843 0.7956488
#> [85] 0.8355704 0.8015311 0.8894352 0.2295197 0.9445218 0.7201368 0.8188090
#> [92] 0.7463717 0.6928422 0.9730670 0.2295197 0.5092100 0.6787133 0.9347920
#> [99] 0.5749436 0.6095136 0.9589464 0.0000000 0.0000000 0.0000000 0.0000000
#> [106] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [183] 0.0000000 0.0000000 0.0000000
#>
#> $Time
#> 63 136 197 169 6 57 129 92 5 97 92.1 158 5.1
#> 22.77 21.83 21.60 22.41 15.64 14.46 23.41 22.92 16.43 19.14 22.92 20.14 16.43
#> 51 77 170 159 183 127 56 51.1 57.1 78 97.1 77.1 76
#> 18.23 7.27 19.54 10.55 9.24 3.53 12.21 18.23 14.46 23.88 19.14 7.27 19.22
#> 63.1 36 18 14 90 110 85 78.1 8 187 167 133 128
#> 22.77 21.19 15.21 12.89 20.94 17.56 16.44 23.88 18.43 9.92 15.55 14.65 20.35
#> 145 99 170.1 192 23 136.1 63.2 128.1 63.3 110.1 134 130 136.2
#> 10.07 21.19 19.54 16.44 16.92 21.83 22.77 20.35 22.77 17.56 17.81 16.47 21.83
#> 150 8.1 190 130.1 153 197.1 29 170.2 39 139 15 6.1 167.1
#> 20.33 18.43 20.81 16.47 21.33 21.60 15.45 19.54 15.59 21.49 22.68 15.64 15.55
#> 159.1 40 77.2 32 179 105 157 32.1 169.1 187.1 41 8.2 16
#> 10.55 18.00 7.27 20.90 18.63 19.75 15.10 20.90 22.41 9.92 18.02 18.43 8.71
#> 77.3 167.2 197.2 13 139.1 181 26 85.1 133.1 92.2 101 88 5.2
#> 7.27 15.55 21.60 14.34 21.49 16.46 15.77 16.44 14.65 22.92 9.97 18.37 16.43
#> 40.1 8.3 149 92.3 99.1 179.1 93 128.2 158.1 183.1 151 17 94
#> 18.00 18.43 8.37 22.92 21.19 18.63 10.33 20.35 20.14 9.24 24.00 24.00 24.00
#> 193 173 98 74 109 83 138 65 72 109.1 200 72.1 165
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135 122 121 84 131 38 84.1 27 126 173.1 103 109.2 95
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87 28 82 119 12 112 148 200.1 83.1 72.2 103.1 120 118
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 22 152 34 65.1 53 131.1 9 191 48 98.1 135.1 151.1 198
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75 176 165.1 121.1 141 162 126.1 20 75.1 162.1 182 72.3 28.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98.2 191.1 46 122.1 185 135.2 94.1 72.4 65.2 196 102 7 126.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34.1 160 75.2
#> 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[54]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01053243 0.57931961 0.25688388
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.295112901 0.001457563 0.188008486
#> grade_iii, Cure model
#> 0.964636886
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 128 20.35 1 35 0 1
#> 40 18.00 1 28 1 0
#> 128.1 20.35 1 35 0 1
#> 136 21.83 1 43 0 1
#> 153 21.33 1 55 1 0
#> 107 11.18 1 54 1 0
#> 90 20.94 1 50 0 1
#> 37 12.52 1 57 1 0
#> 169 22.41 1 46 0 0
#> 158 20.14 1 74 1 0
#> 70 7.38 1 30 1 0
#> 6 15.64 1 39 0 0
#> 41 18.02 1 40 1 0
#> 153.1 21.33 1 55 1 0
#> 85 16.44 1 36 0 0
#> 189 10.51 1 NA 1 0
#> 16 8.71 1 71 0 1
#> 13 14.34 1 54 0 1
#> 192 16.44 1 31 1 0
#> 105 19.75 1 60 0 0
#> 39 15.59 1 37 0 1
#> 125 15.65 1 67 1 0
#> 129 23.41 1 53 1 0
#> 99 21.19 1 38 0 1
#> 5 16.43 1 51 0 1
#> 51 18.23 1 83 0 1
#> 157 15.10 1 47 0 0
#> 4 17.64 1 NA 0 1
#> 23 16.92 1 61 0 0
#> 159 10.55 1 50 0 1
#> 26 15.77 1 49 0 1
#> 50 10.02 1 NA 1 0
#> 164 23.60 1 76 0 1
#> 155 13.08 1 26 0 0
#> 86 23.81 1 58 0 1
#> 181 16.46 1 45 0 1
#> 133 14.65 1 57 0 0
#> 133.1 14.65 1 57 0 0
#> 157.1 15.10 1 47 0 0
#> 105.1 19.75 1 60 0 0
#> 91 5.33 1 61 0 1
#> 105.2 19.75 1 60 0 0
#> 92 22.92 1 47 0 1
#> 93 10.33 1 52 0 1
#> 164.1 23.60 1 76 0 1
#> 188 16.16 1 46 0 1
#> 78 23.88 1 43 0 0
#> 127 3.53 1 62 0 1
#> 15 22.68 1 48 0 0
#> 105.3 19.75 1 60 0 0
#> 111 17.45 1 47 0 1
#> 107.1 11.18 1 54 1 0
#> 39.1 15.59 1 37 0 1
#> 58 19.34 1 39 0 0
#> 111.1 17.45 1 47 0 1
#> 197 21.60 1 69 1 0
#> 101 9.97 1 10 0 1
#> 18 15.21 1 49 1 0
#> 24 23.89 1 38 0 0
#> 164.2 23.60 1 76 0 1
#> 166 19.98 1 48 0 0
#> 89 11.44 1 NA 0 0
#> 190 20.81 1 42 1 0
#> 90.1 20.94 1 50 0 1
#> 69 23.23 1 25 0 1
#> 29 15.45 1 68 1 0
#> 49 12.19 1 48 1 0
#> 37.1 12.52 1 57 1 0
#> 168 23.72 1 70 0 0
#> 150 20.33 1 48 0 0
#> 77 7.27 1 67 0 1
#> 199 19.81 1 NA 0 1
#> 101.1 9.97 1 10 0 1
#> 45 17.42 1 54 0 1
#> 69.1 23.23 1 25 0 1
#> 49.1 12.19 1 48 1 0
#> 50.1 10.02 1 NA 1 0
#> 49.2 12.19 1 48 1 0
#> 55 19.34 1 69 0 1
#> 114 13.68 1 NA 0 0
#> 70.1 7.38 1 30 1 0
#> 195 11.76 1 NA 1 0
#> 145 10.07 1 65 1 0
#> 42 12.43 1 49 0 1
#> 89.1 11.44 1 NA 0 0
#> 85.1 16.44 1 36 0 0
#> 36 21.19 1 48 0 1
#> 195.1 11.76 1 NA 1 0
#> 157.2 15.10 1 47 0 0
#> 13.1 14.34 1 54 0 1
#> 57 14.46 1 45 0 1
#> 155.1 13.08 1 26 0 0
#> 158.1 20.14 1 74 1 0
#> 123 13.00 1 44 1 0
#> 79 16.23 1 54 1 0
#> 199.1 19.81 1 NA 0 1
#> 90.2 20.94 1 50 0 1
#> 171 16.57 1 41 0 1
#> 96 14.54 1 33 0 1
#> 167 15.55 1 56 1 0
#> 99.1 21.19 1 38 0 1
#> 100 16.07 1 60 0 0
#> 197.1 21.60 1 69 1 0
#> 180 14.82 1 37 0 0
#> 61 10.12 1 36 0 1
#> 117 17.46 1 26 0 1
#> 60 13.15 1 38 1 0
#> 150.1 20.33 1 48 0 0
#> 16.1 8.71 1 71 0 1
#> 179 18.63 1 42 0 0
#> 168.1 23.72 1 70 0 0
#> 63 22.77 1 31 1 0
#> 98 24.00 0 34 1 0
#> 3 24.00 0 31 1 0
#> 160 24.00 0 31 1 0
#> 126 24.00 0 48 0 0
#> 1 24.00 0 23 1 0
#> 198 24.00 0 66 0 1
#> 94 24.00 0 51 0 1
#> 72 24.00 0 40 0 1
#> 173 24.00 0 19 0 1
#> 141 24.00 0 44 1 0
#> 119 24.00 0 17 0 0
#> 47 24.00 0 38 0 1
#> 143 24.00 0 51 0 0
#> 87 24.00 0 27 0 0
#> 65 24.00 0 57 1 0
#> 198.1 24.00 0 66 0 1
#> 176 24.00 0 43 0 1
#> 33 24.00 0 53 0 0
#> 148 24.00 0 61 1 0
#> 33.1 24.00 0 53 0 0
#> 172 24.00 0 41 0 0
#> 103 24.00 0 56 1 0
#> 132 24.00 0 55 0 0
#> 35 24.00 0 51 0 0
#> 160.1 24.00 0 31 1 0
#> 135 24.00 0 58 1 0
#> 131 24.00 0 66 0 0
#> 28 24.00 0 67 1 0
#> 17 24.00 0 38 0 1
#> 115 24.00 0 NA 1 0
#> 19 24.00 0 57 0 1
#> 38 24.00 0 31 1 0
#> 35.1 24.00 0 51 0 0
#> 34 24.00 0 36 0 0
#> 65.1 24.00 0 57 1 0
#> 165 24.00 0 47 0 0
#> 112 24.00 0 61 0 0
#> 72.1 24.00 0 40 0 1
#> 144 24.00 0 28 0 1
#> 161 24.00 0 45 0 0
#> 20 24.00 0 46 1 0
#> 141.1 24.00 0 44 1 0
#> 12 24.00 0 63 0 0
#> 141.2 24.00 0 44 1 0
#> 102 24.00 0 49 0 0
#> 3.1 24.00 0 31 1 0
#> 72.2 24.00 0 40 0 1
#> 71 24.00 0 51 0 0
#> 112.1 24.00 0 61 0 0
#> 146 24.00 0 63 1 0
#> 148.1 24.00 0 61 1 0
#> 147 24.00 0 76 1 0
#> 84 24.00 0 39 0 1
#> 185 24.00 0 44 1 0
#> 94.1 24.00 0 51 0 1
#> 172.1 24.00 0 41 0 0
#> 67 24.00 0 25 0 0
#> 172.2 24.00 0 41 0 0
#> 102.1 24.00 0 49 0 0
#> 172.3 24.00 0 41 0 0
#> 143.1 24.00 0 51 0 0
#> 115.1 24.00 0 NA 1 0
#> 132.1 24.00 0 55 0 0
#> 48 24.00 0 31 1 0
#> 137 24.00 0 45 1 0
#> 47.1 24.00 0 38 0 1
#> 94.2 24.00 0 51 0 1
#> 112.2 24.00 0 61 0 0
#> 64 24.00 0 43 0 0
#> 118 24.00 0 44 1 0
#> 12.1 24.00 0 63 0 0
#> 46 24.00 0 71 0 0
#> 198.2 24.00 0 66 0 1
#> 146.1 24.00 0 63 1 0
#> 65.2 24.00 0 57 1 0
#> 186 24.00 0 45 1 0
#> 102.2 24.00 0 49 0 0
#> 28.1 24.00 0 67 1 0
#> 19.1 24.00 0 57 0 1
#> 62 24.00 0 71 0 0
#> 193 24.00 0 45 0 1
#> 198.3 24.00 0 66 0 1
#> 112.3 24.00 0 61 0 0
#> 198.4 24.00 0 66 0 1
#> 147.1 24.00 0 76 1 0
#> 161.1 24.00 0 45 0 0
#> 112.4 24.00 0 61 0 0
#> 121 24.00 0 57 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.295 NA NA NA
#> 2 age, Cure model 0.00146 NA NA NA
#> 3 grade_ii, Cure model 0.188 NA NA NA
#> 4 grade_iii, Cure model 0.965 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0105 NA NA NA
#> 2 grade_ii, Survival model 0.579 NA NA NA
#> 3 grade_iii, Survival model 0.257 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.295113 0.001458 0.188008 0.964637
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 258
#> Residual Deviance: 250.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.295112901 0.001457563 0.188008486 0.964636886
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01053243 0.57931961 0.25688388
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.190688719 0.341046261 0.190688719 0.092778609 0.117008533 0.821009346
#> [7] 0.157088889 0.750386337 0.084723270 0.225453313 0.940056256 0.521030494
#> [13] 0.330715843 0.117008533 0.424171131 0.916107384 0.679586469 0.424171131
#> [19] 0.252652442 0.532146858 0.509993458 0.040030160 0.133059694 0.455609541
#> [25] 0.320329917 0.587819881 0.392353024 0.844581907 0.498984710 0.021162661
#> [31] 0.714896682 0.006550716 0.413514672 0.632977698 0.632977698 0.587819881
#> [37] 0.252652442 0.975834062 0.252652442 0.061771629 0.856491168 0.021162661
#> [43] 0.477191560 0.003046057 0.987892862 0.076951986 0.252652442 0.361508339
#> [49] 0.821009346 0.532146858 0.290199168 0.361508339 0.100960769 0.892398970
#> [55] 0.576633663 0.000685009 0.021162661 0.243379696 0.182025839 0.157088889
#> [61] 0.047665825 0.565433270 0.785894970 0.750386337 0.010779276 0.207782317
#> [67] 0.963822755 0.892398970 0.381927502 0.047665825 0.785894970 0.785894970
#> [73] 0.290199168 0.940056256 0.880412523 0.773970072 0.424171131 0.133059694
#> [79] 0.587819881 0.679586469 0.667843094 0.714896682 0.225453313 0.738508195
#> [85] 0.466401871 0.157088889 0.402911543 0.656139880 0.554261195 0.133059694
#> [91] 0.488031149 0.100960769 0.621480392 0.868442364 0.351274784 0.703086063
#> [97] 0.207782317 0.916107384 0.310096828 0.010779276 0.069480496 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000
#>
#> $Time
#> 128 40 128.1 136 153 107 90 37 169 158 70 6 41
#> 20.35 18.00 20.35 21.83 21.33 11.18 20.94 12.52 22.41 20.14 7.38 15.64 18.02
#> 153.1 85 16 13 192 105 39 125 129 99 5 51 157
#> 21.33 16.44 8.71 14.34 16.44 19.75 15.59 15.65 23.41 21.19 16.43 18.23 15.10
#> 23 159 26 164 155 86 181 133 133.1 157.1 105.1 91 105.2
#> 16.92 10.55 15.77 23.60 13.08 23.81 16.46 14.65 14.65 15.10 19.75 5.33 19.75
#> 92 93 164.1 188 78 127 15 105.3 111 107.1 39.1 58 111.1
#> 22.92 10.33 23.60 16.16 23.88 3.53 22.68 19.75 17.45 11.18 15.59 19.34 17.45
#> 197 101 18 24 164.2 166 190 90.1 69 29 49 37.1 168
#> 21.60 9.97 15.21 23.89 23.60 19.98 20.81 20.94 23.23 15.45 12.19 12.52 23.72
#> 150 77 101.1 45 69.1 49.1 49.2 55 70.1 145 42 85.1 36
#> 20.33 7.27 9.97 17.42 23.23 12.19 12.19 19.34 7.38 10.07 12.43 16.44 21.19
#> 157.2 13.1 57 155.1 158.1 123 79 90.2 171 96 167 99.1 100
#> 15.10 14.34 14.46 13.08 20.14 13.00 16.23 20.94 16.57 14.54 15.55 21.19 16.07
#> 197.1 180 61 117 60 150.1 16.1 179 168.1 63 98 3 160
#> 21.60 14.82 10.12 17.46 13.15 20.33 8.71 18.63 23.72 22.77 24.00 24.00 24.00
#> 126 1 198 94 72 173 141 119 47 143 87 65 198.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176 33 148 33.1 172 103 132 35 160.1 135 131 28 17
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 19 38 35.1 34 65.1 165 112 72.1 144 161 20 141.1 12
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 141.2 102 3.1 72.2 71 112.1 146 148.1 147 84 185 94.1 172.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67 172.2 102.1 172.3 143.1 132.1 48 137 47.1 94.2 112.2 64 118
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12.1 46 198.2 146.1 65.2 186 102.2 28.1 19.1 62 193 198.3 112.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 198.4 147.1 161.1 112.4 121
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[55]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.001402052 0.588896534 0.355810945
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.030850417 -0.003781511 -0.180427242
#> grade_iii, Cure model
#> 1.057950951
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 50 10.02 1 NA 1 0
#> 183 9.24 1 67 1 0
#> 100 16.07 1 60 0 0
#> 52 10.42 1 52 0 1
#> 123 13.00 1 44 1 0
#> 105 19.75 1 60 0 0
#> 150 20.33 1 48 0 0
#> 180 14.82 1 37 0 0
#> 36 21.19 1 48 0 1
#> 129 23.41 1 53 1 0
#> 16 8.71 1 71 0 1
#> 25 6.32 1 34 1 0
#> 97 19.14 1 65 0 1
#> 199 19.81 1 NA 0 1
#> 86 23.81 1 58 0 1
#> 60 13.15 1 38 1 0
#> 175 21.91 1 43 0 0
#> 108 18.29 1 39 0 1
#> 43 12.10 1 61 0 1
#> 50.1 10.02 1 NA 1 0
#> 105.1 19.75 1 60 0 0
#> 41 18.02 1 40 1 0
#> 5 16.43 1 51 0 1
#> 45 17.42 1 54 0 1
#> 199.1 19.81 1 NA 0 1
#> 14 12.89 1 21 0 0
#> 16.1 8.71 1 71 0 1
#> 190 20.81 1 42 1 0
#> 68 20.62 1 44 0 0
#> 92 22.92 1 47 0 1
#> 125 15.65 1 67 1 0
#> 76 19.22 1 54 0 1
#> 52.1 10.42 1 52 0 1
#> 78 23.88 1 43 0 0
#> 52.2 10.42 1 52 0 1
#> 140 12.68 1 59 1 0
#> 58 19.34 1 39 0 0
#> 110 17.56 1 65 0 1
#> 108.1 18.29 1 39 0 1
#> 169 22.41 1 46 0 0
#> 57 14.46 1 45 0 1
#> 199.2 19.81 1 NA 0 1
#> 150.1 20.33 1 48 0 0
#> 78.1 23.88 1 43 0 0
#> 192 16.44 1 31 1 0
#> 124 9.73 1 NA 1 0
#> 58.1 19.34 1 39 0 0
#> 6 15.64 1 39 0 0
#> 13 14.34 1 54 0 1
#> 101 9.97 1 10 0 1
#> 199.3 19.81 1 NA 0 1
#> 128 20.35 1 35 0 1
#> 159 10.55 1 50 0 1
#> 41.1 18.02 1 40 1 0
#> 8 18.43 1 32 0 0
#> 134 17.81 1 47 1 0
#> 8.1 18.43 1 32 0 0
#> 166 19.98 1 48 0 0
#> 180.1 14.82 1 37 0 0
#> 105.2 19.75 1 60 0 0
#> 100.1 16.07 1 60 0 0
#> 194 22.40 1 38 0 1
#> 100.2 16.07 1 60 0 0
#> 41.2 18.02 1 40 1 0
#> 114 13.68 1 NA 0 0
#> 194.1 22.40 1 38 0 1
#> 13.1 14.34 1 54 0 1
#> 130 16.47 1 53 0 1
#> 99 21.19 1 38 0 1
#> 171 16.57 1 41 0 1
#> 159.1 10.55 1 50 0 1
#> 61 10.12 1 36 0 1
#> 30 17.43 1 78 0 0
#> 13.2 14.34 1 54 0 1
#> 107 11.18 1 54 1 0
#> 157 15.10 1 47 0 0
#> 111 17.45 1 47 0 1
#> 124.1 9.73 1 NA 1 0
#> 52.3 10.42 1 52 0 1
#> 92.1 22.92 1 47 0 1
#> 15 22.68 1 48 0 0
#> 117 17.46 1 26 0 1
#> 154 12.63 1 20 1 0
#> 170 19.54 1 43 0 1
#> 89 11.44 1 NA 0 0
#> 155 13.08 1 26 0 0
#> 61.1 10.12 1 36 0 1
#> 188 16.16 1 46 0 1
#> 86.1 23.81 1 58 0 1
#> 117.1 17.46 1 26 0 1
#> 39 15.59 1 37 0 1
#> 76.1 19.22 1 54 0 1
#> 68.1 20.62 1 44 0 0
#> 91 5.33 1 61 0 1
#> 41.3 18.02 1 40 1 0
#> 14.1 12.89 1 21 0 0
#> 86.2 23.81 1 58 0 1
#> 5.1 16.43 1 51 0 1
#> 45.1 17.42 1 54 0 1
#> 26 15.77 1 49 0 1
#> 89.1 11.44 1 NA 0 0
#> 56 12.21 1 60 0 0
#> 42 12.43 1 49 0 1
#> 159.2 10.55 1 50 0 1
#> 32 20.90 1 37 1 0
#> 51 18.23 1 83 0 1
#> 166.1 19.98 1 48 0 0
#> 150.2 20.33 1 48 0 0
#> 18 15.21 1 49 1 0
#> 36.1 21.19 1 48 0 1
#> 77 7.27 1 67 0 1
#> 123.1 13.00 1 44 1 0
#> 84 24.00 0 39 0 1
#> 112 24.00 0 61 0 0
#> 33 24.00 0 53 0 0
#> 17 24.00 0 38 0 1
#> 34 24.00 0 36 0 0
#> 87 24.00 0 27 0 0
#> 1 24.00 0 23 1 0
#> 48 24.00 0 31 1 0
#> 156 24.00 0 50 1 0
#> 28 24.00 0 67 1 0
#> 144 24.00 0 28 0 1
#> 22 24.00 0 52 1 0
#> 67 24.00 0 25 0 0
#> 165 24.00 0 47 0 0
#> 34.1 24.00 0 36 0 0
#> 196 24.00 0 19 0 0
#> 47 24.00 0 38 0 1
#> 75 24.00 0 21 1 0
#> 27 24.00 0 63 1 0
#> 178 24.00 0 52 1 0
#> 12 24.00 0 63 0 0
#> 62 24.00 0 71 0 0
#> 22.1 24.00 0 52 1 0
#> 142 24.00 0 53 0 0
#> 178.1 24.00 0 52 1 0
#> 38 24.00 0 31 1 0
#> 116 24.00 0 58 0 1
#> 21 24.00 0 47 0 0
#> 31 24.00 0 36 0 1
#> 193 24.00 0 45 0 1
#> 161 24.00 0 45 0 0
#> 161.1 24.00 0 45 0 0
#> 95 24.00 0 68 0 1
#> 120 24.00 0 68 0 1
#> 135 24.00 0 58 1 0
#> 186 24.00 0 45 1 0
#> 72 24.00 0 40 0 1
#> 98 24.00 0 34 1 0
#> 120.1 24.00 0 68 0 1
#> 132 24.00 0 55 0 0
#> 62.1 24.00 0 71 0 0
#> 53 24.00 0 32 0 1
#> 72.1 24.00 0 40 0 1
#> 46 24.00 0 71 0 0
#> 161.2 24.00 0 45 0 0
#> 22.2 24.00 0 52 1 0
#> 7 24.00 0 37 1 0
#> 31.1 24.00 0 36 0 1
#> 72.2 24.00 0 40 0 1
#> 196.1 24.00 0 19 0 0
#> 118 24.00 0 44 1 0
#> 28.1 24.00 0 67 1 0
#> 65 24.00 0 57 1 0
#> 54 24.00 0 53 1 0
#> 198 24.00 0 66 0 1
#> 198.1 24.00 0 66 0 1
#> 121 24.00 0 57 1 0
#> 46.1 24.00 0 71 0 0
#> 126 24.00 0 48 0 0
#> 119 24.00 0 17 0 0
#> 2 24.00 0 9 0 0
#> 174 24.00 0 49 1 0
#> 67.1 24.00 0 25 0 0
#> 35 24.00 0 51 0 0
#> 182 24.00 0 35 0 0
#> 200 24.00 0 64 0 0
#> 94 24.00 0 51 0 1
#> 165.1 24.00 0 47 0 0
#> 28.2 24.00 0 67 1 0
#> 163 24.00 0 66 0 0
#> 34.2 24.00 0 36 0 0
#> 165.2 24.00 0 47 0 0
#> 191 24.00 0 60 0 1
#> 95.1 24.00 0 68 0 1
#> 126.1 24.00 0 48 0 0
#> 21.1 24.00 0 47 0 0
#> 74 24.00 0 43 0 1
#> 174.1 24.00 0 49 1 0
#> 174.2 24.00 0 49 1 0
#> 82 24.00 0 34 0 0
#> 143 24.00 0 51 0 0
#> 7.1 24.00 0 37 1 0
#> 138 24.00 0 44 1 0
#> 121.1 24.00 0 57 1 0
#> 67.2 24.00 0 25 0 0
#> 46.2 24.00 0 71 0 0
#> 176 24.00 0 43 0 1
#> 132.1 24.00 0 55 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.0309 NA NA NA
#> 2 age, Cure model -0.00378 NA NA NA
#> 3 grade_ii, Cure model -0.180 NA NA NA
#> 4 grade_iii, Cure model 1.06 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00140 NA NA NA
#> 2 grade_ii, Survival model 0.589 NA NA NA
#> 3 grade_iii, Survival model 0.356 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.030850 -0.003782 -0.180427 1.057951
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 261.1
#> Residual Deviance: 247.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.030850417 -0.003781511 -0.180427242 1.057950951
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.001402052 0.588896534 0.355810945
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.95908249 0.68165100 0.91041012 0.81523773 0.38481368 0.33218147
#> [7] 0.75363796 0.24224731 0.13178894 0.96598914 0.98646361 0.46732872
#> [13] 0.08460629 0.79998005 0.22913379 0.49732730 0.87457276 0.38481368
#> [19] 0.52658737 0.65711818 0.61484730 0.83016651 0.96598914 0.28832034
#> [25] 0.29947837 0.14782239 0.71390943 0.44713707 0.91041012 0.03300026
#> [31] 0.91041012 0.84508727 0.42644138 0.57114623 0.49732730 0.18943404
#> [37] 0.76928867 0.33218147 0.03300026 0.64877703 0.42644138 0.72191825
#> [43] 0.77711262 0.95212678 0.32127802 0.88912199 0.52658737 0.47741193
#> [49] 0.56216675 0.47741193 0.36362376 0.75363796 0.38481368 0.68165100
#> [55] 0.20356942 0.68165100 0.52658737 0.20356942 0.77711262 0.64034020
#> [61] 0.24224731 0.63184320 0.88912199 0.93822087 0.60615932 0.77711262
#> [67] 0.88187569 0.74576280 0.59745693 0.91041012 0.14782239 0.17522858
#> [73] 0.58004686 0.85251780 0.41593594 0.80761023 0.93822087 0.67347467
#> [79] 0.08460629 0.58004686 0.72992208 0.44713707 0.29947837 0.99324460
#> [85] 0.52658737 0.83016651 0.08460629 0.65711818 0.61484730 0.70581163
#> [91] 0.86723584 0.85989347 0.88912199 0.27675452 0.51684611 0.36362376
#> [97] 0.33218147 0.73788198 0.24224731 0.97964089 0.81523773 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 183 100 52 123 105 150 180 36 129 16 25 97 86
#> 9.24 16.07 10.42 13.00 19.75 20.33 14.82 21.19 23.41 8.71 6.32 19.14 23.81
#> 60 175 108 43 105.1 41 5 45 14 16.1 190 68 92
#> 13.15 21.91 18.29 12.10 19.75 18.02 16.43 17.42 12.89 8.71 20.81 20.62 22.92
#> 125 76 52.1 78 52.2 140 58 110 108.1 169 57 150.1 78.1
#> 15.65 19.22 10.42 23.88 10.42 12.68 19.34 17.56 18.29 22.41 14.46 20.33 23.88
#> 192 58.1 6 13 101 128 159 41.1 8 134 8.1 166 180.1
#> 16.44 19.34 15.64 14.34 9.97 20.35 10.55 18.02 18.43 17.81 18.43 19.98 14.82
#> 105.2 100.1 194 100.2 41.2 194.1 13.1 130 99 171 159.1 61 30
#> 19.75 16.07 22.40 16.07 18.02 22.40 14.34 16.47 21.19 16.57 10.55 10.12 17.43
#> 13.2 107 157 111 52.3 92.1 15 117 154 170 155 61.1 188
#> 14.34 11.18 15.10 17.45 10.42 22.92 22.68 17.46 12.63 19.54 13.08 10.12 16.16
#> 86.1 117.1 39 76.1 68.1 91 41.3 14.1 86.2 5.1 45.1 26 56
#> 23.81 17.46 15.59 19.22 20.62 5.33 18.02 12.89 23.81 16.43 17.42 15.77 12.21
#> 42 159.2 32 51 166.1 150.2 18 36.1 77 123.1 84 112 33
#> 12.43 10.55 20.90 18.23 19.98 20.33 15.21 21.19 7.27 13.00 24.00 24.00 24.00
#> 17 34 87 1 48 156 28 144 22 67 165 34.1 196
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 47 75 27 178 12 62 22.1 142 178.1 38 116 21 31
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193 161 161.1 95 120 135 186 72 98 120.1 132 62.1 53
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72.1 46 161.2 22.2 7 31.1 72.2 196.1 118 28.1 65 54 198
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 198.1 121 46.1 126 119 2 174 67.1 35 182 200 94 165.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28.2 163 34.2 165.2 191 95.1 126.1 21.1 74 174.1 174.2 82 143
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 7.1 138 121.1 67.2 46.2 176 132.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[56]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.001879788 0.472263463 0.873388129
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.69562015 0.01550538 -0.06424231
#> grade_iii, Cure model
#> 0.57423015
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 59 10.16 1 NA 1 0
#> 166 19.98 1 48 0 0
#> 195 11.76 1 NA 1 0
#> 91 5.33 1 61 0 1
#> 93 10.33 1 52 0 1
#> 63 22.77 1 31 1 0
#> 158 20.14 1 74 1 0
#> 124 9.73 1 NA 1 0
#> 101 9.97 1 10 0 1
#> 63.1 22.77 1 31 1 0
#> 125 15.65 1 67 1 0
#> 139 21.49 1 63 1 0
#> 189 10.51 1 NA 1 0
#> 127 3.53 1 62 0 1
#> 10 10.53 1 34 0 0
#> 40 18.00 1 28 1 0
#> 184 17.77 1 38 0 0
#> 133 14.65 1 57 0 0
#> 133.1 14.65 1 57 0 0
#> 197 21.60 1 69 1 0
#> 96 14.54 1 33 0 1
#> 92 22.92 1 47 0 1
#> 129 23.41 1 53 1 0
#> 145 10.07 1 65 1 0
#> 183 9.24 1 67 1 0
#> 154 12.63 1 20 1 0
#> 78 23.88 1 43 0 0
#> 197.1 21.60 1 69 1 0
#> 85 16.44 1 36 0 0
#> 197.2 21.60 1 69 1 0
#> 139.1 21.49 1 63 1 0
#> 60 13.15 1 38 1 0
#> 40.1 18.00 1 28 1 0
#> 40.2 18.00 1 28 1 0
#> 89 11.44 1 NA 0 0
#> 78.1 23.88 1 43 0 0
#> 117 17.46 1 26 0 1
#> 150 20.33 1 48 0 0
#> 177 12.53 1 75 0 0
#> 57 14.46 1 45 0 1
#> 52 10.42 1 52 0 1
#> 93.1 10.33 1 52 0 1
#> 97 19.14 1 65 0 1
#> 15 22.68 1 48 0 0
#> 139.2 21.49 1 63 1 0
#> 15.1 22.68 1 48 0 0
#> 77 7.27 1 67 0 1
#> 89.1 11.44 1 NA 0 0
#> 130 16.47 1 53 0 1
#> 190 20.81 1 42 1 0
#> 183.1 9.24 1 67 1 0
#> 41 18.02 1 40 1 0
#> 55 19.34 1 69 0 1
#> 171 16.57 1 41 0 1
#> 25 6.32 1 34 1 0
#> 171.1 16.57 1 41 0 1
#> 16 8.71 1 71 0 1
#> 90 20.94 1 50 0 1
#> 183.2 9.24 1 67 1 0
#> 180 14.82 1 37 0 0
#> 51 18.23 1 83 0 1
#> 97.1 19.14 1 65 0 1
#> 26 15.77 1 49 0 1
#> 134 17.81 1 47 1 0
#> 124.1 9.73 1 NA 1 0
#> 26.1 15.77 1 49 0 1
#> 127.1 3.53 1 62 0 1
#> 167 15.55 1 56 1 0
#> 32 20.90 1 37 1 0
#> 134.1 17.81 1 47 1 0
#> 90.1 20.94 1 50 0 1
#> 92.1 22.92 1 47 0 1
#> 78.2 23.88 1 43 0 0
#> 166.1 19.98 1 48 0 0
#> 168 23.72 1 70 0 0
#> 4 17.64 1 NA 0 1
#> 45 17.42 1 54 0 1
#> 169 22.41 1 46 0 0
#> 124.2 9.73 1 NA 1 0
#> 24 23.89 1 38 0 0
#> 45.1 17.42 1 54 0 1
#> 42 12.43 1 49 0 1
#> 61 10.12 1 36 0 1
#> 61.1 10.12 1 36 0 1
#> 18 15.21 1 49 1 0
#> 192 16.44 1 31 1 0
#> 40.3 18.00 1 28 1 0
#> 199 19.81 1 NA 0 1
#> 63.2 22.77 1 31 1 0
#> 136 21.83 1 43 0 1
#> 68 20.62 1 44 0 0
#> 192.1 16.44 1 31 1 0
#> 15.2 22.68 1 48 0 0
#> 55.1 19.34 1 69 0 1
#> 68.1 20.62 1 44 0 0
#> 37 12.52 1 57 1 0
#> 130.1 16.47 1 53 0 1
#> 123 13.00 1 44 1 0
#> 40.4 18.00 1 28 1 0
#> 111 17.45 1 47 0 1
#> 39 15.59 1 37 0 1
#> 92.2 22.92 1 47 0 1
#> 93.2 10.33 1 52 0 1
#> 23 16.92 1 61 0 0
#> 129.1 23.41 1 53 1 0
#> 169.1 22.41 1 46 0 0
#> 32.1 20.90 1 37 1 0
#> 150.1 20.33 1 48 0 0
#> 81 14.06 1 34 0 0
#> 166.2 19.98 1 48 0 0
#> 157 15.10 1 47 0 0
#> 23.1 16.92 1 61 0 0
#> 176 24.00 0 43 0 1
#> 74 24.00 0 43 0 1
#> 196 24.00 0 19 0 0
#> 196.1 24.00 0 19 0 0
#> 109 24.00 0 48 0 0
#> 141 24.00 0 44 1 0
#> 74.1 24.00 0 43 0 1
#> 173 24.00 0 19 0 1
#> 137 24.00 0 45 1 0
#> 156 24.00 0 50 1 0
#> 138 24.00 0 44 1 0
#> 53 24.00 0 32 0 1
#> 163 24.00 0 66 0 0
#> 121 24.00 0 57 1 0
#> 118 24.00 0 44 1 0
#> 7 24.00 0 37 1 0
#> 132 24.00 0 55 0 0
#> 38 24.00 0 31 1 0
#> 11 24.00 0 42 0 1
#> 19 24.00 0 57 0 1
#> 53.1 24.00 0 32 0 1
#> 103 24.00 0 56 1 0
#> 151 24.00 0 42 0 0
#> 104 24.00 0 50 1 0
#> 131 24.00 0 66 0 0
#> 31 24.00 0 36 0 1
#> 102 24.00 0 49 0 0
#> 48 24.00 0 31 1 0
#> 72 24.00 0 40 0 1
#> 48.1 24.00 0 31 1 0
#> 95 24.00 0 68 0 1
#> 72.1 24.00 0 40 0 1
#> 54 24.00 0 53 1 0
#> 118.1 24.00 0 44 1 0
#> 120 24.00 0 68 0 1
#> 112 24.00 0 61 0 0
#> 102.1 24.00 0 49 0 0
#> 73 24.00 0 NA 0 1
#> 71 24.00 0 51 0 0
#> 161 24.00 0 45 0 0
#> 67 24.00 0 25 0 0
#> 162 24.00 0 51 0 0
#> 28 24.00 0 67 1 0
#> 1 24.00 0 23 1 0
#> 103.1 24.00 0 56 1 0
#> 160 24.00 0 31 1 0
#> 27 24.00 0 63 1 0
#> 84 24.00 0 39 0 1
#> 109.1 24.00 0 48 0 0
#> 28.1 24.00 0 67 1 0
#> 71.1 24.00 0 51 0 0
#> 156.1 24.00 0 50 1 0
#> 174 24.00 0 49 1 0
#> 46 24.00 0 71 0 0
#> 137.1 24.00 0 45 1 0
#> 71.2 24.00 0 51 0 0
#> 186 24.00 0 45 1 0
#> 47 24.00 0 38 0 1
#> 104.1 24.00 0 50 1 0
#> 1.1 24.00 0 23 1 0
#> 115 24.00 0 NA 1 0
#> 54.1 24.00 0 53 1 0
#> 148 24.00 0 61 1 0
#> 191 24.00 0 60 0 1
#> 161.1 24.00 0 45 0 0
#> 141.1 24.00 0 44 1 0
#> 172 24.00 0 41 0 0
#> 144 24.00 0 28 0 1
#> 7.1 24.00 0 37 1 0
#> 22 24.00 0 52 1 0
#> 28.2 24.00 0 67 1 0
#> 115.1 24.00 0 NA 1 0
#> 143 24.00 0 51 0 0
#> 163.1 24.00 0 66 0 0
#> 162.1 24.00 0 51 0 0
#> 185 24.00 0 44 1 0
#> 94 24.00 0 51 0 1
#> 196.2 24.00 0 19 0 0
#> 17 24.00 0 38 0 1
#> 162.2 24.00 0 51 0 0
#> 196.3 24.00 0 19 0 0
#> 121.1 24.00 0 57 1 0
#> 54.2 24.00 0 53 1 0
#> 98 24.00 0 34 1 0
#> 31.1 24.00 0 36 0 1
#> 54.3 24.00 0 53 1 0
#> 102.2 24.00 0 49 0 0
#> 178 24.00 0 52 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.696 NA NA NA
#> 2 age, Cure model 0.0155 NA NA NA
#> 3 grade_ii, Cure model -0.0642 NA NA NA
#> 4 grade_iii, Cure model 0.574 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00188 NA NA NA
#> 2 grade_ii, Survival model 0.472 NA NA NA
#> 3 grade_iii, Survival model 0.873 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.69562 0.01551 -0.06424 0.57423
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 257.7
#> Residual Deviance: 252.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.69562015 0.01550538 -0.06424231 0.57423015
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.001879788 0.472263463 0.873388129
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.55181135 0.98443359 0.91306109 0.27039987 0.54230613 0.94670940
#> [7] 0.27039987 0.79611163 0.42247539 0.98969330 0.90125900 0.63088599
#> [13] 0.68461047 0.83412696 0.83412696 0.38823686 0.84662873 0.22632169
#> [19] 0.18127107 0.94115422 0.95221802 0.87725441 0.07546750 0.38823686
#> [25] 0.76333178 0.38823686 0.42247539 0.86509144 0.63088599 0.63088599
#> [31] 0.07546750 0.69232357 0.52318225 0.88329238 0.85283169 0.90719154
#> [37] 0.91306109 0.59746202 0.30998434 0.42247539 0.30998434 0.97379807
#> [43] 0.74986951 0.49427192 0.95221802 0.62266391 0.57970519 0.73599735
#> [49] 0.97912608 0.73599735 0.96841955 0.45461873 0.95221802 0.82784179
#> [55] 0.61436192 0.59746202 0.78317984 0.66925844 0.78317984 0.98969330
#> [61] 0.80893000 0.47474288 0.66925844 0.45461873 0.22632169 0.07546750
#> [67] 0.55181135 0.15097073 0.70736316 0.34910449 0.02974445 0.70736316
#> [73] 0.89532389 0.93002345 0.93002345 0.81526012 0.76333178 0.63088599
#> [79] 0.27039987 0.37551699 0.50399223 0.76333178 0.30998434 0.57970519
#> [85] 0.50399223 0.88932411 0.74986951 0.87118867 0.63088599 0.69990865
#> [91] 0.80256093 0.22632169 0.91306109 0.72169751 0.18127107 0.34910449
#> [97] 0.47474288 0.52318225 0.85896301 0.55181135 0.82155318 0.72169751
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000
#>
#> $Time
#> 166 91 93 63 158 101 63.1 125 139 127 10 40 184
#> 19.98 5.33 10.33 22.77 20.14 9.97 22.77 15.65 21.49 3.53 10.53 18.00 17.77
#> 133 133.1 197 96 92 129 145 183 154 78 197.1 85 197.2
#> 14.65 14.65 21.60 14.54 22.92 23.41 10.07 9.24 12.63 23.88 21.60 16.44 21.60
#> 139.1 60 40.1 40.2 78.1 117 150 177 57 52 93.1 97 15
#> 21.49 13.15 18.00 18.00 23.88 17.46 20.33 12.53 14.46 10.42 10.33 19.14 22.68
#> 139.2 15.1 77 130 190 183.1 41 55 171 25 171.1 16 90
#> 21.49 22.68 7.27 16.47 20.81 9.24 18.02 19.34 16.57 6.32 16.57 8.71 20.94
#> 183.2 180 51 97.1 26 134 26.1 127.1 167 32 134.1 90.1 92.1
#> 9.24 14.82 18.23 19.14 15.77 17.81 15.77 3.53 15.55 20.90 17.81 20.94 22.92
#> 78.2 166.1 168 45 169 24 45.1 42 61 61.1 18 192 40.3
#> 23.88 19.98 23.72 17.42 22.41 23.89 17.42 12.43 10.12 10.12 15.21 16.44 18.00
#> 63.2 136 68 192.1 15.2 55.1 68.1 37 130.1 123 40.4 111 39
#> 22.77 21.83 20.62 16.44 22.68 19.34 20.62 12.52 16.47 13.00 18.00 17.45 15.59
#> 92.2 93.2 23 129.1 169.1 32.1 150.1 81 166.2 157 23.1 176 74
#> 22.92 10.33 16.92 23.41 22.41 20.90 20.33 14.06 19.98 15.10 16.92 24.00 24.00
#> 196 196.1 109 141 74.1 173 137 156 138 53 163 121 118
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 7 132 38 11 19 53.1 103 151 104 131 31 102 48
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72 48.1 95 72.1 54 118.1 120 112 102.1 71 161 67 162
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28 1 103.1 160 27 84 109.1 28.1 71.1 156.1 174 46 137.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71.2 186 47 104.1 1.1 54.1 148 191 161.1 141.1 172 144 7.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 22 28.2 143 163.1 162.1 185 94 196.2 17 162.2 196.3 121.1 54.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98 31.1 54.3 102.2 178
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[57]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.0001448995 0.7414452832 0.4636963007
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.82415665 0.02219934 -0.22325238
#> grade_iii, Cure model
#> 0.21883334
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 78 23.88 1 43 0 0
#> 150 20.33 1 48 0 0
#> 85 16.44 1 36 0 0
#> 155 13.08 1 26 0 0
#> 124 9.73 1 NA 1 0
#> 23 16.92 1 61 0 0
#> 155.1 13.08 1 26 0 0
#> 99 21.19 1 38 0 1
#> 180 14.82 1 37 0 0
#> 177 12.53 1 75 0 0
#> 129 23.41 1 53 1 0
#> 127 3.53 1 62 0 1
#> 81 14.06 1 34 0 0
#> 111 17.45 1 47 0 1
#> 189 10.51 1 NA 1 0
#> 60 13.15 1 38 1 0
#> 108 18.29 1 39 0 1
#> 153 21.33 1 55 1 0
#> 16 8.71 1 71 0 1
#> 113 22.86 1 34 0 0
#> 166 19.98 1 48 0 0
#> 197 21.60 1 69 1 0
#> 41 18.02 1 40 1 0
#> 110 17.56 1 65 0 1
#> 114 13.68 1 NA 0 0
#> 155.2 13.08 1 26 0 0
#> 181 16.46 1 45 0 1
#> 150.1 20.33 1 48 0 0
#> 15 22.68 1 48 0 0
#> 125 15.65 1 67 1 0
#> 58 19.34 1 39 0 0
#> 24 23.89 1 38 0 0
#> 140 12.68 1 59 1 0
#> 181.1 16.46 1 45 0 1
#> 124.1 9.73 1 NA 1 0
#> 187 9.92 1 39 1 0
#> 171 16.57 1 41 0 1
#> 52 10.42 1 52 0 1
#> 86 23.81 1 58 0 1
#> 36 21.19 1 48 0 1
#> 150.2 20.33 1 48 0 0
#> 114.1 13.68 1 NA 0 0
#> 61 10.12 1 36 0 1
#> 136 21.83 1 43 0 1
#> 79 16.23 1 54 1 0
#> 179 18.63 1 42 0 0
#> 190 20.81 1 42 1 0
#> 30 17.43 1 78 0 0
#> 199 19.81 1 NA 0 1
#> 105 19.75 1 60 0 0
#> 10 10.53 1 34 0 0
#> 101 9.97 1 10 0 1
#> 36.1 21.19 1 48 0 1
#> 43 12.10 1 61 0 1
#> 110.1 17.56 1 65 0 1
#> 136.1 21.83 1 43 0 1
#> 100 16.07 1 60 0 0
#> 79.1 16.23 1 54 1 0
#> 192 16.44 1 31 1 0
#> 30.1 17.43 1 78 0 0
#> 140.1 12.68 1 59 1 0
#> 188 16.16 1 46 0 1
#> 52.1 10.42 1 52 0 1
#> 150.3 20.33 1 48 0 0
#> 166.1 19.98 1 48 0 0
#> 184 17.77 1 38 0 0
#> 88 18.37 1 47 0 0
#> 157 15.10 1 47 0 0
#> 49 12.19 1 48 1 0
#> 195 11.76 1 NA 1 0
#> 56 12.21 1 60 0 0
#> 36.2 21.19 1 48 0 1
#> 29 15.45 1 68 1 0
#> 123 13.00 1 44 1 0
#> 96 14.54 1 33 0 1
#> 40 18.00 1 28 1 0
#> 66 22.13 1 53 0 0
#> 187.1 9.92 1 39 1 0
#> 171.1 16.57 1 41 0 1
#> 59 10.16 1 NA 1 0
#> 16.1 8.71 1 71 0 1
#> 43.1 12.10 1 61 0 1
#> 117 17.46 1 26 0 1
#> 154 12.63 1 20 1 0
#> 76 19.22 1 54 0 1
#> 60.1 13.15 1 38 1 0
#> 101.1 9.97 1 10 0 1
#> 88.1 18.37 1 47 0 0
#> 8 18.43 1 32 0 0
#> 13 14.34 1 54 0 1
#> 29.1 15.45 1 68 1 0
#> 159 10.55 1 50 0 1
#> 24.1 23.89 1 38 0 0
#> 88.2 18.37 1 47 0 0
#> 166.2 19.98 1 48 0 0
#> 39 15.59 1 37 0 1
#> 128 20.35 1 35 0 1
#> 15.1 22.68 1 48 0 0
#> 123.1 13.00 1 44 1 0
#> 123.2 13.00 1 44 1 0
#> 79.2 16.23 1 54 1 0
#> 79.3 16.23 1 54 1 0
#> 56.1 12.21 1 60 0 0
#> 107 11.18 1 54 1 0
#> 59.1 10.16 1 NA 1 0
#> 107.1 11.18 1 54 1 0
#> 4 17.64 1 NA 0 1
#> 42 12.43 1 49 0 1
#> 36.3 21.19 1 48 0 1
#> 18 15.21 1 49 1 0
#> 130 16.47 1 53 0 1
#> 181.2 16.46 1 45 0 1
#> 119 24.00 0 17 0 0
#> 143 24.00 0 51 0 0
#> 7 24.00 0 37 1 0
#> 94 24.00 0 51 0 1
#> 178 24.00 0 52 1 0
#> 38 24.00 0 31 1 0
#> 73 24.00 0 NA 0 1
#> 174 24.00 0 49 1 0
#> 7.1 24.00 0 37 1 0
#> 72 24.00 0 40 0 1
#> 67 24.00 0 25 0 0
#> 120 24.00 0 68 0 1
#> 72.1 24.00 0 40 0 1
#> 196 24.00 0 19 0 0
#> 176 24.00 0 43 0 1
#> 176.1 24.00 0 43 0 1
#> 135 24.00 0 58 1 0
#> 71 24.00 0 51 0 0
#> 152 24.00 0 36 0 1
#> 137 24.00 0 45 1 0
#> 143.1 24.00 0 51 0 0
#> 161 24.00 0 45 0 0
#> 135.1 24.00 0 58 1 0
#> 31 24.00 0 36 0 1
#> 73.1 24.00 0 NA 0 1
#> 48 24.00 0 31 1 0
#> 17 24.00 0 38 0 1
#> 156 24.00 0 50 1 0
#> 173 24.00 0 19 0 1
#> 200 24.00 0 64 0 0
#> 95 24.00 0 68 0 1
#> 34 24.00 0 36 0 0
#> 9 24.00 0 31 1 0
#> 126 24.00 0 48 0 0
#> 160 24.00 0 31 1 0
#> 185 24.00 0 44 1 0
#> 48.1 24.00 0 31 1 0
#> 20 24.00 0 46 1 0
#> 121 24.00 0 57 1 0
#> 67.1 24.00 0 25 0 0
#> 74 24.00 0 43 0 1
#> 67.2 24.00 0 25 0 0
#> 173.1 24.00 0 19 0 1
#> 20.1 24.00 0 46 1 0
#> 196.1 24.00 0 19 0 0
#> 116 24.00 0 58 0 1
#> 198 24.00 0 66 0 1
#> 147 24.00 0 76 1 0
#> 135.2 24.00 0 58 1 0
#> 75 24.00 0 21 1 0
#> 162 24.00 0 51 0 0
#> 185.1 24.00 0 44 1 0
#> 9.1 24.00 0 31 1 0
#> 7.2 24.00 0 37 1 0
#> 62 24.00 0 71 0 0
#> 160.1 24.00 0 31 1 0
#> 17.1 24.00 0 38 0 1
#> 53 24.00 0 32 0 1
#> 11 24.00 0 42 0 1
#> 3 24.00 0 31 1 0
#> 135.3 24.00 0 58 1 0
#> 1 24.00 0 23 1 0
#> 172 24.00 0 41 0 0
#> 142 24.00 0 53 0 0
#> 95.1 24.00 0 68 0 1
#> 53.1 24.00 0 32 0 1
#> 141 24.00 0 44 1 0
#> 84 24.00 0 39 0 1
#> 119.1 24.00 0 17 0 0
#> 182 24.00 0 35 0 0
#> 119.2 24.00 0 17 0 0
#> 142.1 24.00 0 53 0 0
#> 198.1 24.00 0 66 0 1
#> 82 24.00 0 34 0 0
#> 62.1 24.00 0 71 0 0
#> 12 24.00 0 63 0 0
#> 161.1 24.00 0 45 0 0
#> 64 24.00 0 43 0 0
#> 12.1 24.00 0 63 0 0
#> 138 24.00 0 44 1 0
#> 173.2 24.00 0 19 0 1
#> 112 24.00 0 61 0 0
#> 115 24.00 0 NA 1 0
#> 152.1 24.00 0 36 0 1
#> 112.1 24.00 0 61 0 0
#> 102 24.00 0 49 0 0
#> 102.1 24.00 0 49 0 0
#> 72.2 24.00 0 40 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.824 NA NA NA
#> 2 age, Cure model 0.0222 NA NA NA
#> 3 grade_ii, Cure model -0.223 NA NA NA
#> 4 grade_iii, Cure model 0.219 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.000145 NA NA NA
#> 2 grade_ii, Survival model 0.741 NA NA NA
#> 3 grade_iii, Survival model 0.464 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.8242 0.0222 -0.2233 0.2188
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 257.7
#> Residual Deviance: 252.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.82415665 0.02219934 -0.22325238 0.21883334
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.0001448995 0.7414452832 0.4636963007
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.06026571 0.31865737 0.63242835 0.79212713 0.56921321 0.79212713
#> [7] 0.24490105 0.74623463 0.85761921 0.10493521 0.99350813 0.76944727
#> [13] 0.54115809 0.77713962 0.47271941 0.23162087 0.98051812 0.12198428
#> [19] 0.35910439 0.21746259 0.48298077 0.51263584 0.79212713 0.60608014
#> [25] 0.31865737 0.13904898 0.69882072 0.40046138 0.02204844 0.83623315
#> [31] 0.60608014 0.96742862 0.57861840 0.93397336 0.08426933 0.24490105
#> [37] 0.31865737 0.94742281 0.18807623 0.64985389 0.42141694 0.29719921
#> [43] 0.55056094 0.38990807 0.92716740 0.95414372 0.24490105 0.89289828
#> [49] 0.51263584 0.18807623 0.69059775 0.64985389 0.63242835 0.55056094
#> [55] 0.83623315 0.68237563 0.93397336 0.31865737 0.35910439 0.50282266
#> [61] 0.44222257 0.73845147 0.88588625 0.87179725 0.24490105 0.71500667
#> [67] 0.81450414 0.75401823 0.49301055 0.17116863 0.96742862 0.57861840
#> [73] 0.98051812 0.89289828 0.53165966 0.85051402 0.41101628 0.77713962
#> [79] 0.95414372 0.44222257 0.43181917 0.76175531 0.71500667 0.92036168
#> [85] 0.02204844 0.44222257 0.35910439 0.70694063 0.30803698 0.13904898
#> [91] 0.81450414 0.81450414 0.64985389 0.64985389 0.87179725 0.90674253
#> [97] 0.90674253 0.86472505 0.24490105 0.73066887 0.59693314 0.60608014
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000
#>
#> $Time
#> 78 150 85 155 23 155.1 99 180 177 129 127 81 111
#> 23.88 20.33 16.44 13.08 16.92 13.08 21.19 14.82 12.53 23.41 3.53 14.06 17.45
#> 60 108 153 16 113 166 197 41 110 155.2 181 150.1 15
#> 13.15 18.29 21.33 8.71 22.86 19.98 21.60 18.02 17.56 13.08 16.46 20.33 22.68
#> 125 58 24 140 181.1 187 171 52 86 36 150.2 61 136
#> 15.65 19.34 23.89 12.68 16.46 9.92 16.57 10.42 23.81 21.19 20.33 10.12 21.83
#> 79 179 190 30 105 10 101 36.1 43 110.1 136.1 100 79.1
#> 16.23 18.63 20.81 17.43 19.75 10.53 9.97 21.19 12.10 17.56 21.83 16.07 16.23
#> 192 30.1 140.1 188 52.1 150.3 166.1 184 88 157 49 56 36.2
#> 16.44 17.43 12.68 16.16 10.42 20.33 19.98 17.77 18.37 15.10 12.19 12.21 21.19
#> 29 123 96 40 66 187.1 171.1 16.1 43.1 117 154 76 60.1
#> 15.45 13.00 14.54 18.00 22.13 9.92 16.57 8.71 12.10 17.46 12.63 19.22 13.15
#> 101.1 88.1 8 13 29.1 159 24.1 88.2 166.2 39 128 15.1 123.1
#> 9.97 18.37 18.43 14.34 15.45 10.55 23.89 18.37 19.98 15.59 20.35 22.68 13.00
#> 123.2 79.2 79.3 56.1 107 107.1 42 36.3 18 130 181.2 119 143
#> 13.00 16.23 16.23 12.21 11.18 11.18 12.43 21.19 15.21 16.47 16.46 24.00 24.00
#> 7 94 178 38 174 7.1 72 67 120 72.1 196 176 176.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135 71 152 137 143.1 161 135.1 31 48 17 156 173 200
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95 34 9 126 160 185 48.1 20 121 67.1 74 67.2 173.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20.1 196.1 116 198 147 135.2 75 162 185.1 9.1 7.2 62 160.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 17.1 53 11 3 135.3 1 172 142 95.1 53.1 141 84 119.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 182 119.2 142.1 198.1 82 62.1 12 161.1 64 12.1 138 173.2 112
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152.1 112.1 102 102.1 72.2
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[58]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.02099732 0.35106693 0.42376108
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.00479053 0.01534703 0.29172198
#> grade_iii, Cure model
#> 1.13458802
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 66 22.13 1 53 0 0
#> 24 23.89 1 38 0 0
#> 36 21.19 1 48 0 1
#> 110 17.56 1 65 0 1
#> 166 19.98 1 48 0 0
#> 106 16.67 1 49 1 0
#> 69 23.23 1 25 0 1
#> 110.1 17.56 1 65 0 1
#> 56 12.21 1 60 0 0
#> 39 15.59 1 37 0 1
#> 99 21.19 1 38 0 1
#> 79 16.23 1 54 1 0
#> 195 11.76 1 NA 1 0
#> 158 20.14 1 74 1 0
#> 29 15.45 1 68 1 0
#> 68 20.62 1 44 0 0
#> 42 12.43 1 49 0 1
#> 93 10.33 1 52 0 1
#> 171 16.57 1 41 0 1
#> 113 22.86 1 34 0 0
#> 99.1 21.19 1 38 0 1
#> 92 22.92 1 47 0 1
#> 78 23.88 1 43 0 0
#> 93.1 10.33 1 52 0 1
#> 169 22.41 1 46 0 0
#> 166.1 19.98 1 48 0 0
#> 136 21.83 1 43 0 1
#> 81 14.06 1 34 0 0
#> 43 12.10 1 61 0 1
#> 63 22.77 1 31 1 0
#> 97 19.14 1 65 0 1
#> 157 15.10 1 47 0 0
#> 81.1 14.06 1 34 0 0
#> 55 19.34 1 69 0 1
#> 5 16.43 1 51 0 1
#> 40 18.00 1 28 1 0
#> 100 16.07 1 60 0 0
#> 68.1 20.62 1 44 0 0
#> 6 15.64 1 39 0 0
#> 90 20.94 1 50 0 1
#> 181 16.46 1 45 0 1
#> 184 17.77 1 38 0 0
#> 63.1 22.77 1 31 1 0
#> 183 9.24 1 67 1 0
#> 43.1 12.10 1 61 0 1
#> 32 20.90 1 37 1 0
#> 42.1 12.43 1 49 0 1
#> 101 9.97 1 10 0 1
#> 194 22.40 1 38 0 1
#> 170 19.54 1 43 0 1
#> 50 10.02 1 NA 1 0
#> 49 12.19 1 48 1 0
#> 52 10.42 1 52 0 1
#> 26 15.77 1 49 0 1
#> 91 5.33 1 61 0 1
#> 117 17.46 1 26 0 1
#> 124 9.73 1 NA 1 0
#> 69.1 23.23 1 25 0 1
#> 59 10.16 1 NA 1 0
#> 130 16.47 1 53 0 1
#> 69.2 23.23 1 25 0 1
#> 69.3 23.23 1 25 0 1
#> 107 11.18 1 54 1 0
#> 63.2 22.77 1 31 1 0
#> 136.1 21.83 1 43 0 1
#> 190 20.81 1 42 1 0
#> 40.1 18.00 1 28 1 0
#> 5.1 16.43 1 51 0 1
#> 18 15.21 1 49 1 0
#> 129 23.41 1 53 1 0
#> 51 18.23 1 83 0 1
#> 79.1 16.23 1 54 1 0
#> 158.1 20.14 1 74 1 0
#> 106.1 16.67 1 49 1 0
#> 97.1 19.14 1 65 0 1
#> 43.2 12.10 1 61 0 1
#> 79.2 16.23 1 54 1 0
#> 25 6.32 1 34 1 0
#> 37 12.52 1 57 1 0
#> 129.1 23.41 1 53 1 0
#> 97.2 19.14 1 65 0 1
#> 194.1 22.40 1 38 0 1
#> 59.1 10.16 1 NA 1 0
#> 61 10.12 1 36 0 1
#> 169.1 22.41 1 46 0 0
#> 195.1 11.76 1 NA 1 0
#> 197 21.60 1 69 1 0
#> 139 21.49 1 63 1 0
#> 39.1 15.59 1 37 0 1
#> 136.2 21.83 1 43 0 1
#> 134 17.81 1 47 1 0
#> 105 19.75 1 60 0 0
#> 24.1 23.89 1 38 0 0
#> 81.2 14.06 1 34 0 0
#> 29.1 15.45 1 68 1 0
#> 92.1 22.92 1 47 0 1
#> 10 10.53 1 34 0 0
#> 93.2 10.33 1 52 0 1
#> 123 13.00 1 44 1 0
#> 4 17.64 1 NA 0 1
#> 89 11.44 1 NA 0 0
#> 145 10.07 1 65 1 0
#> 79.3 16.23 1 54 1 0
#> 139.1 21.49 1 63 1 0
#> 105.1 19.75 1 60 0 0
#> 93.3 10.33 1 52 0 1
#> 60 13.15 1 38 1 0
#> 59.2 10.16 1 NA 1 0
#> 45 17.42 1 54 0 1
#> 107.1 11.18 1 54 1 0
#> 89.1 11.44 1 NA 0 0
#> 187 9.92 1 39 1 0
#> 176 24.00 0 43 0 1
#> 75 24.00 0 21 1 0
#> 1 24.00 0 23 1 0
#> 19 24.00 0 57 0 1
#> 73 24.00 0 NA 0 1
#> 115 24.00 0 NA 1 0
#> 31 24.00 0 36 0 1
#> 33 24.00 0 53 0 0
#> 9 24.00 0 31 1 0
#> 116 24.00 0 58 0 1
#> 103 24.00 0 56 1 0
#> 64 24.00 0 43 0 0
#> 3 24.00 0 31 1 0
#> 9.1 24.00 0 31 1 0
#> 46 24.00 0 71 0 0
#> 22 24.00 0 52 1 0
#> 28 24.00 0 67 1 0
#> 138 24.00 0 44 1 0
#> 135 24.00 0 58 1 0
#> 148 24.00 0 61 1 0
#> 64.1 24.00 0 43 0 0
#> 71 24.00 0 51 0 0
#> 48 24.00 0 31 1 0
#> 73.1 24.00 0 NA 0 1
#> 71.1 24.00 0 51 0 0
#> 28.1 24.00 0 67 1 0
#> 112 24.00 0 61 0 0
#> 64.2 24.00 0 43 0 0
#> 191 24.00 0 60 0 1
#> 35 24.00 0 51 0 0
#> 87 24.00 0 27 0 0
#> 115.1 24.00 0 NA 1 0
#> 83 24.00 0 6 0 0
#> 131 24.00 0 66 0 0
#> 22.1 24.00 0 52 1 0
#> 176.1 24.00 0 43 0 1
#> 11 24.00 0 42 0 1
#> 174 24.00 0 49 1 0
#> 2 24.00 0 9 0 0
#> 35.1 24.00 0 51 0 0
#> 71.2 24.00 0 51 0 0
#> 54 24.00 0 53 1 0
#> 200 24.00 0 64 0 0
#> 103.1 24.00 0 56 1 0
#> 141 24.00 0 44 1 0
#> 95 24.00 0 68 0 1
#> 191.1 24.00 0 60 0 1
#> 118 24.00 0 44 1 0
#> 72 24.00 0 40 0 1
#> 75.1 24.00 0 21 1 0
#> 121 24.00 0 57 1 0
#> 48.1 24.00 0 31 1 0
#> 67 24.00 0 25 0 0
#> 35.2 24.00 0 51 0 0
#> 38 24.00 0 31 1 0
#> 34 24.00 0 36 0 0
#> 53 24.00 0 32 0 1
#> 65 24.00 0 57 1 0
#> 163 24.00 0 66 0 0
#> 121.1 24.00 0 57 1 0
#> 178 24.00 0 52 1 0
#> 160 24.00 0 31 1 0
#> 182 24.00 0 35 0 0
#> 178.1 24.00 0 52 1 0
#> 11.1 24.00 0 42 0 1
#> 173 24.00 0 19 0 1
#> 21 24.00 0 47 0 0
#> 31.1 24.00 0 36 0 1
#> 135.1 24.00 0 58 1 0
#> 74 24.00 0 43 0 1
#> 3.1 24.00 0 31 1 0
#> 104 24.00 0 50 1 0
#> 72.1 24.00 0 40 0 1
#> 126 24.00 0 48 0 0
#> 148.1 24.00 0 61 1 0
#> 148.2 24.00 0 61 1 0
#> 73.2 24.00 0 NA 0 1
#> 173.1 24.00 0 19 0 1
#> 122 24.00 0 66 0 0
#> 161 24.00 0 45 0 0
#> 182.1 24.00 0 35 0 0
#> 74.1 24.00 0 43 0 1
#> 165 24.00 0 47 0 0
#> 176.2 24.00 0 43 0 1
#> 67.1 24.00 0 25 0 0
#> 143 24.00 0 51 0 0
#> 94 24.00 0 51 0 1
#> 151 24.00 0 42 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.00 NA NA NA
#> 2 age, Cure model 0.0153 NA NA NA
#> 3 grade_ii, Cure model 0.292 NA NA NA
#> 4 grade_iii, Cure model 1.13 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0210 NA NA NA
#> 2 grade_ii, Survival model 0.351 NA NA NA
#> 3 grade_iii, Survival model 0.424 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.00479 0.01535 0.29172 1.13459
#>
#> Degrees of Freedom: 184 Total (i.e. Null); 181 Residual
#> Null Deviance: 254.5
#> Residual Deviance: 242.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.00479053 0.01534703 0.29172198 1.13458802
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.02099732 0.35106693 0.42376108
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.6336951 0.2092349 0.6969894 0.8344094 0.7641486 0.8510329 0.4314124
#> [8] 0.8344094 0.9462913 0.9021522 0.6969894 0.8779494 0.7522766 0.9088318
#> [15] 0.7392269 0.9403160 0.9716719 0.8589625 0.5339418 0.6969894 0.5035095
#> [22] 0.3282356 0.9716719 0.5873965 0.7641486 0.6444580 0.9216501 0.9522020
#> [29] 0.5489297 0.7976119 0.9184734 0.9216501 0.7923309 0.8705641 0.8165371
#> [36] 0.8918621 0.7392269 0.8987476 0.7185736 0.8667514 0.8299910 0.5489297
#> [43] 0.9924669 0.9522020 0.7256023 0.9403160 0.9873324 0.6115918 0.7868486
#> [50] 0.9492599 0.9689392 0.8953265 0.9975119 0.8427823 0.4314124 0.8628890
#> [57] 0.4314124 0.4314124 0.9606496 0.5489297 0.6444580 0.7324916 0.8165371
#> [64] 0.8705641 0.9152780 0.3793587 0.8119421 0.8779494 0.7522766 0.8510329
#> [71] 0.7976119 0.9522020 0.8779494 0.9949955 0.9372600 0.3793587 0.7976119
#> [78] 0.6115918 0.9821400 0.5873965 0.6724000 0.6812205 0.9021522 0.6444580
#> [85] 0.8255437 0.7757082 0.2092349 0.9216501 0.9088318 0.5035095 0.9661788
#> [92] 0.9716719 0.9341665 0.9847518 0.8779494 0.6812205 0.7757082 0.9716719
#> [99] 0.9310465 0.8469452 0.9606496 0.9899071 0.0000000 0.0000000 0.0000000
#> [106] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [183] 0.0000000 0.0000000 0.0000000
#>
#> $Time
#> 66 24 36 110 166 106 69 110.1 56 39 99 79 158
#> 22.13 23.89 21.19 17.56 19.98 16.67 23.23 17.56 12.21 15.59 21.19 16.23 20.14
#> 29 68 42 93 171 113 99.1 92 78 93.1 169 166.1 136
#> 15.45 20.62 12.43 10.33 16.57 22.86 21.19 22.92 23.88 10.33 22.41 19.98 21.83
#> 81 43 63 97 157 81.1 55 5 40 100 68.1 6 90
#> 14.06 12.10 22.77 19.14 15.10 14.06 19.34 16.43 18.00 16.07 20.62 15.64 20.94
#> 181 184 63.1 183 43.1 32 42.1 101 194 170 49 52 26
#> 16.46 17.77 22.77 9.24 12.10 20.90 12.43 9.97 22.40 19.54 12.19 10.42 15.77
#> 91 117 69.1 130 69.2 69.3 107 63.2 136.1 190 40.1 5.1 18
#> 5.33 17.46 23.23 16.47 23.23 23.23 11.18 22.77 21.83 20.81 18.00 16.43 15.21
#> 129 51 79.1 158.1 106.1 97.1 43.2 79.2 25 37 129.1 97.2 194.1
#> 23.41 18.23 16.23 20.14 16.67 19.14 12.10 16.23 6.32 12.52 23.41 19.14 22.40
#> 61 169.1 197 139 39.1 136.2 134 105 24.1 81.2 29.1 92.1 10
#> 10.12 22.41 21.60 21.49 15.59 21.83 17.81 19.75 23.89 14.06 15.45 22.92 10.53
#> 93.2 123 145 79.3 139.1 105.1 93.3 60 45 107.1 187 176 75
#> 10.33 13.00 10.07 16.23 21.49 19.75 10.33 13.15 17.42 11.18 9.92 24.00 24.00
#> 1 19 31 33 9 116 103 64 3 9.1 46 22 28
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 138 135 148 64.1 71 48 71.1 28.1 112 64.2 191 35 87
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 83 131 22.1 176.1 11 174 2 35.1 71.2 54 200 103.1 141
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95 191.1 118 72 75.1 121 48.1 67 35.2 38 34 53 65
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 163 121.1 178 160 182 178.1 11.1 173 21 31.1 135.1 74 3.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 104 72.1 126 148.1 148.2 173.1 122 161 182.1 74.1 165 176.2 67.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143 94 151
#> 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[59]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.002662556 0.581245172 0.589567757
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.071391731 -0.001062665 -0.025804789
#> grade_iii, Cure model
#> 1.078378357
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 108 18.29 1 39 0 1
#> 101 9.97 1 10 0 1
#> 106 16.67 1 49 1 0
#> 43 12.10 1 61 0 1
#> 10 10.53 1 34 0 0
#> 127 3.53 1 62 0 1
#> 76 19.22 1 54 0 1
#> 32 20.90 1 37 1 0
#> 37 12.52 1 57 1 0
#> 157 15.10 1 47 0 0
#> 37.1 12.52 1 57 1 0
#> 107 11.18 1 54 1 0
#> 133 14.65 1 57 0 0
#> 24 23.89 1 38 0 0
#> 192 16.44 1 31 1 0
#> 52 10.42 1 52 0 1
#> 194 22.40 1 38 0 1
#> 110 17.56 1 65 0 1
#> 39 15.59 1 37 0 1
#> 77 7.27 1 67 0 1
#> 70 7.38 1 30 1 0
#> 168 23.72 1 70 0 0
#> 179 18.63 1 42 0 0
#> 184 17.77 1 38 0 0
#> 29 15.45 1 68 1 0
#> 4 17.64 1 NA 0 1
#> 124 9.73 1 NA 1 0
#> 68 20.62 1 44 0 0
#> 8 18.43 1 32 0 0
#> 42 12.43 1 49 0 1
#> 100 16.07 1 60 0 0
#> 70.1 7.38 1 30 1 0
#> 39.1 15.59 1 37 0 1
#> 66 22.13 1 53 0 0
#> 189 10.51 1 NA 1 0
#> 128 20.35 1 35 0 1
#> 89 11.44 1 NA 0 0
#> 13 14.34 1 54 0 1
#> 134 17.81 1 47 1 0
#> 42.1 12.43 1 49 0 1
#> 99 21.19 1 38 0 1
#> 55 19.34 1 69 0 1
#> 153 21.33 1 55 1 0
#> 105 19.75 1 60 0 0
#> 179.1 18.63 1 42 0 0
#> 88 18.37 1 47 0 0
#> 128.1 20.35 1 35 0 1
#> 129 23.41 1 53 1 0
#> 52.1 10.42 1 52 0 1
#> 8.1 18.43 1 32 0 0
#> 16 8.71 1 71 0 1
#> 50 10.02 1 NA 1 0
#> 139 21.49 1 63 1 0
#> 150 20.33 1 48 0 0
#> 37.2 12.52 1 57 1 0
#> 77.1 7.27 1 67 0 1
#> 57 14.46 1 45 0 1
#> 4.1 17.64 1 NA 0 1
#> 63 22.77 1 31 1 0
#> 158 20.14 1 74 1 0
#> 70.2 7.38 1 30 1 0
#> 93 10.33 1 52 0 1
#> 5 16.43 1 51 0 1
#> 39.2 15.59 1 37 0 1
#> 24.1 23.89 1 38 0 0
#> 192.1 16.44 1 31 1 0
#> 189.1 10.51 1 NA 1 0
#> 195 11.76 1 NA 1 0
#> 169 22.41 1 46 0 0
#> 140 12.68 1 59 1 0
#> 85 16.44 1 36 0 0
#> 164 23.60 1 76 0 1
#> 14 12.89 1 21 0 0
#> 41 18.02 1 40 1 0
#> 117 17.46 1 26 0 1
#> 58 19.34 1 39 0 0
#> 140.1 12.68 1 59 1 0
#> 139.1 21.49 1 63 1 0
#> 23 16.92 1 61 0 0
#> 58.1 19.34 1 39 0 0
#> 159 10.55 1 50 0 1
#> 133.1 14.65 1 57 0 0
#> 96 14.54 1 33 0 1
#> 145 10.07 1 65 1 0
#> 99.1 21.19 1 38 0 1
#> 51 18.23 1 83 0 1
#> 58.2 19.34 1 39 0 0
#> 90 20.94 1 50 0 1
#> 88.1 18.37 1 47 0 0
#> 77.2 7.27 1 67 0 1
#> 13.1 14.34 1 54 0 1
#> 113 22.86 1 34 0 0
#> 153.1 21.33 1 55 1 0
#> 90.1 20.94 1 50 0 1
#> 133.2 14.65 1 57 0 0
#> 194.1 22.40 1 38 0 1
#> 39.3 15.59 1 37 0 1
#> 114 13.68 1 NA 0 0
#> 187 9.92 1 39 1 0
#> 179.2 18.63 1 42 0 0
#> 113.1 22.86 1 34 0 0
#> 60 13.15 1 38 1 0
#> 32.1 20.90 1 37 1 0
#> 69 23.23 1 25 0 1
#> 155 13.08 1 26 0 0
#> 187.1 9.92 1 39 1 0
#> 18 15.21 1 49 1 0
#> 49 12.19 1 48 1 0
#> 127.1 3.53 1 62 0 1
#> 124.1 9.73 1 NA 1 0
#> 113.2 22.86 1 34 0 0
#> 18.1 15.21 1 49 1 0
#> 174 24.00 0 49 1 0
#> 83 24.00 0 6 0 0
#> 98 24.00 0 34 1 0
#> 44 24.00 0 56 0 0
#> 20 24.00 0 46 1 0
#> 103 24.00 0 56 1 0
#> 146 24.00 0 63 1 0
#> 151 24.00 0 42 0 0
#> 35 24.00 0 51 0 0
#> 135 24.00 0 58 1 0
#> 178 24.00 0 52 1 0
#> 83.1 24.00 0 6 0 0
#> 21 24.00 0 47 0 0
#> 163 24.00 0 66 0 0
#> 17 24.00 0 38 0 1
#> 95 24.00 0 68 0 1
#> 162 24.00 0 51 0 0
#> 135.1 24.00 0 58 1 0
#> 142 24.00 0 53 0 0
#> 94 24.00 0 51 0 1
#> 121 24.00 0 57 1 0
#> 178.1 24.00 0 52 1 0
#> 146.1 24.00 0 63 1 0
#> 3 24.00 0 31 1 0
#> 122 24.00 0 66 0 0
#> 182 24.00 0 35 0 0
#> 135.2 24.00 0 58 1 0
#> 163.1 24.00 0 66 0 0
#> 118 24.00 0 44 1 0
#> 80 24.00 0 41 0 0
#> 141 24.00 0 44 1 0
#> 193 24.00 0 45 0 1
#> 104 24.00 0 50 1 0
#> 47 24.00 0 38 0 1
#> 103.1 24.00 0 56 1 0
#> 44.1 24.00 0 56 0 0
#> 21.1 24.00 0 47 0 0
#> 22 24.00 0 52 1 0
#> 141.1 24.00 0 44 1 0
#> 137 24.00 0 45 1 0
#> 53 24.00 0 32 0 1
#> 103.2 24.00 0 56 1 0
#> 65 24.00 0 57 1 0
#> 144 24.00 0 28 0 1
#> 46 24.00 0 71 0 0
#> 33 24.00 0 53 0 0
#> 156 24.00 0 50 1 0
#> 87 24.00 0 27 0 0
#> 34 24.00 0 36 0 0
#> 118.1 24.00 0 44 1 0
#> 196 24.00 0 19 0 0
#> 152 24.00 0 36 0 1
#> 19 24.00 0 57 0 1
#> 172 24.00 0 41 0 0
#> 12 24.00 0 63 0 0
#> 121.1 24.00 0 57 1 0
#> 120 24.00 0 68 0 1
#> 17.1 24.00 0 38 0 1
#> 132 24.00 0 55 0 0
#> 151.1 24.00 0 42 0 0
#> 135.3 24.00 0 58 1 0
#> 95.1 24.00 0 68 0 1
#> 87.1 24.00 0 27 0 0
#> 94.1 24.00 0 51 0 1
#> 35.1 24.00 0 51 0 0
#> 22.1 24.00 0 52 1 0
#> 54 24.00 0 53 1 0
#> 87.2 24.00 0 27 0 0
#> 172.1 24.00 0 41 0 0
#> 119 24.00 0 17 0 0
#> 11 24.00 0 42 0 1
#> 7 24.00 0 37 1 0
#> 143 24.00 0 51 0 0
#> 148 24.00 0 61 1 0
#> 121.2 24.00 0 57 1 0
#> 47.1 24.00 0 38 0 1
#> 118.2 24.00 0 44 1 0
#> 200 24.00 0 64 0 0
#> 75 24.00 0 21 1 0
#> 135.4 24.00 0 58 1 0
#> 7.1 24.00 0 37 1 0
#> 73 24.00 0 NA 0 1
#> 161 24.00 0 45 0 0
#> 87.3 24.00 0 27 0 0
#> 178.2 24.00 0 52 1 0
#> 143.1 24.00 0 51 0 0
#> 143.2 24.00 0 51 0 0
#> 87.4 24.00 0 27 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.0714 NA NA NA
#> 2 age, Cure model -0.00106 NA NA NA
#> 3 grade_ii, Cure model -0.0258 NA NA NA
#> 4 grade_iii, Cure model 1.08 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00266 NA NA NA
#> 2 grade_ii, Survival model 0.581 NA NA NA
#> 3 grade_iii, Survival model 0.590 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.071392 -0.001063 -0.025805 1.078378
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.8
#> Residual Deviance: 250.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.071391731 -0.001062665 -0.025804789 1.078378357
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.002662556 0.581245172 0.589567757
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.59147460 0.93136658 0.65808140 0.88232481 0.90100669 0.98890291
#> [7] 0.52112895 0.40761037 0.84403103 0.75483531 0.84403103 0.88859851
#> [13] 0.76194415 0.03779182 0.66604383 0.90718397 0.27124319 0.63375908
#> [19] 0.70445644 0.97209209 0.95493856 0.09330426 0.53008507 0.62545925
#> [25] 0.73340361 0.42771635 0.55634745 0.86330386 0.69678861 0.95493856
#> [31] 0.70445644 0.29983145 0.43786037 0.79693951 0.61714768 0.86330386
#> [37] 0.36407339 0.48557342 0.34019369 0.47616491 0.53008507 0.57394683
#> [43] 0.43786037 0.14933809 0.90718397 0.55634745 0.94908705 0.31437603
#> [49] 0.45705288 0.84403103 0.97209209 0.78999001 0.23817388 0.46672408
#> [55] 0.95493856 0.91932007 0.68910614 0.70445644 0.03779182 0.66604383
#> [61] 0.25477823 0.83080528 0.66604383 0.12501698 0.82404789 0.60871959
#> [67] 0.64193640 0.48557342 0.83080528 0.31437603 0.65001774 0.48557342
#> [73] 0.89482540 0.76194415 0.78297679 0.92536540 0.36407339 0.60017446
#> [79] 0.48557342 0.38649077 0.57394683 0.97209209 0.79693951 0.18874116
#> [85] 0.34019369 0.38649077 0.76194415 0.27124319 0.70445644 0.93733500
#> [91] 0.53008507 0.18874116 0.81052272 0.40761037 0.17009221 0.81728731
#> [97] 0.93733500 0.74066687 0.87600070 0.98890291 0.18874116 0.74066687
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 108 101 106 43 10 127 76 32 37 157 37.1 107 133
#> 18.29 9.97 16.67 12.10 10.53 3.53 19.22 20.90 12.52 15.10 12.52 11.18 14.65
#> 24 192 52 194 110 39 77 70 168 179 184 29 68
#> 23.89 16.44 10.42 22.40 17.56 15.59 7.27 7.38 23.72 18.63 17.77 15.45 20.62
#> 8 42 100 70.1 39.1 66 128 13 134 42.1 99 55 153
#> 18.43 12.43 16.07 7.38 15.59 22.13 20.35 14.34 17.81 12.43 21.19 19.34 21.33
#> 105 179.1 88 128.1 129 52.1 8.1 16 139 150 37.2 77.1 57
#> 19.75 18.63 18.37 20.35 23.41 10.42 18.43 8.71 21.49 20.33 12.52 7.27 14.46
#> 63 158 70.2 93 5 39.2 24.1 192.1 169 140 85 164 14
#> 22.77 20.14 7.38 10.33 16.43 15.59 23.89 16.44 22.41 12.68 16.44 23.60 12.89
#> 41 117 58 140.1 139.1 23 58.1 159 133.1 96 145 99.1 51
#> 18.02 17.46 19.34 12.68 21.49 16.92 19.34 10.55 14.65 14.54 10.07 21.19 18.23
#> 58.2 90 88.1 77.2 13.1 113 153.1 90.1 133.2 194.1 39.3 187 179.2
#> 19.34 20.94 18.37 7.27 14.34 22.86 21.33 20.94 14.65 22.40 15.59 9.92 18.63
#> 113.1 60 32.1 69 155 187.1 18 49 127.1 113.2 18.1 174 83
#> 22.86 13.15 20.90 23.23 13.08 9.92 15.21 12.19 3.53 22.86 15.21 24.00 24.00
#> 98 44 20 103 146 151 35 135 178 83.1 21 163 17
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95 162 135.1 142 94 121 178.1 146.1 3 122 182 135.2 163.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 118 80 141 193 104 47 103.1 44.1 21.1 22 141.1 137 53
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103.2 65 144 46 33 156 87 34 118.1 196 152 19 172
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12 121.1 120 17.1 132 151.1 135.3 95.1 87.1 94.1 35.1 22.1 54
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87.2 172.1 119 11 7 143 148 121.2 47.1 118.2 200 75 135.4
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 7.1 161 87.3 178.2 143.1 143.2 87.4
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[60]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01307040 0.06103614 0.08635746
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.80454871 0.01467708 0.19572147
#> grade_iii, Cure model
#> 0.70037923
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 96 14.54 1 33 0 1
#> 16 8.71 1 71 0 1
#> 6 15.64 1 39 0 0
#> 188 16.16 1 46 0 1
#> 134 17.81 1 47 1 0
#> 139 21.49 1 63 1 0
#> 166 19.98 1 48 0 0
#> 183 9.24 1 67 1 0
#> 57 14.46 1 45 0 1
#> 79 16.23 1 54 1 0
#> 129 23.41 1 53 1 0
#> 136 21.83 1 43 0 1
#> 40 18.00 1 28 1 0
#> 50 10.02 1 NA 1 0
#> 111 17.45 1 47 0 1
#> 157 15.10 1 47 0 0
#> 66 22.13 1 53 0 0
#> 41 18.02 1 40 1 0
#> 164 23.60 1 76 0 1
#> 168 23.72 1 70 0 0
#> 40.1 18.00 1 28 1 0
#> 79.1 16.23 1 54 1 0
#> 168.1 23.72 1 70 0 0
#> 60 13.15 1 38 1 0
#> 177 12.53 1 75 0 0
#> 32 20.90 1 37 1 0
#> 57.1 14.46 1 45 0 1
#> 8 18.43 1 32 0 0
#> 159 10.55 1 50 0 1
#> 155 13.08 1 26 0 0
#> 16.1 8.71 1 71 0 1
#> 177.1 12.53 1 75 0 0
#> 168.2 23.72 1 70 0 0
#> 81 14.06 1 34 0 0
#> 14 12.89 1 21 0 0
#> 42 12.43 1 49 0 1
#> 97 19.14 1 65 0 1
#> 79.2 16.23 1 54 1 0
#> 59 10.16 1 NA 1 0
#> 40.2 18.00 1 28 1 0
#> 139.1 21.49 1 63 1 0
#> 180 14.82 1 37 0 0
#> 69 23.23 1 25 0 1
#> 158 20.14 1 74 1 0
#> 63 22.77 1 31 1 0
#> 197 21.60 1 69 1 0
#> 97.1 19.14 1 65 0 1
#> 45 17.42 1 54 0 1
#> 171 16.57 1 41 0 1
#> 153 21.33 1 55 1 0
#> 96.1 14.54 1 33 0 1
#> 37 12.52 1 57 1 0
#> 45.1 17.42 1 54 0 1
#> 190 20.81 1 42 1 0
#> 195 11.76 1 NA 1 0
#> 86 23.81 1 58 0 1
#> 189 10.51 1 NA 1 0
#> 16.2 8.71 1 71 0 1
#> 100 16.07 1 60 0 0
#> 86.1 23.81 1 58 0 1
#> 111.1 17.45 1 47 0 1
#> 199 19.81 1 NA 0 1
#> 129.1 23.41 1 53 1 0
#> 10 10.53 1 34 0 0
#> 93 10.33 1 52 0 1
#> 6.1 15.64 1 39 0 0
#> 30 17.43 1 78 0 0
#> 69.1 23.23 1 25 0 1
#> 166.1 19.98 1 48 0 0
#> 159.1 10.55 1 50 0 1
#> 97.2 19.14 1 65 0 1
#> 136.1 21.83 1 43 0 1
#> 32.1 20.90 1 37 1 0
#> 181 16.46 1 45 0 1
#> 58 19.34 1 39 0 0
#> 70 7.38 1 30 1 0
#> 159.2 10.55 1 50 0 1
#> 130 16.47 1 53 0 1
#> 110 17.56 1 65 0 1
#> 70.1 7.38 1 30 1 0
#> 108 18.29 1 39 0 1
#> 124 9.73 1 NA 1 0
#> 169 22.41 1 46 0 0
#> 10.1 10.53 1 34 0 0
#> 106 16.67 1 49 1 0
#> 166.2 19.98 1 48 0 0
#> 55 19.34 1 69 0 1
#> 43 12.10 1 61 0 1
#> 8.1 18.43 1 32 0 0
#> 37.1 12.52 1 57 1 0
#> 96.2 14.54 1 33 0 1
#> 78 23.88 1 43 0 0
#> 124.1 9.73 1 NA 1 0
#> 111.2 17.45 1 47 0 1
#> 150 20.33 1 48 0 0
#> 187 9.92 1 39 1 0
#> 40.3 18.00 1 28 1 0
#> 180.1 14.82 1 37 0 0
#> 6.2 15.64 1 39 0 0
#> 164.1 23.60 1 76 0 1
#> 23 16.92 1 61 0 0
#> 85 16.44 1 36 0 0
#> 124.2 9.73 1 NA 1 0
#> 124.3 9.73 1 NA 1 0
#> 153.1 21.33 1 55 1 0
#> 184 17.77 1 38 0 0
#> 39 15.59 1 37 0 1
#> 52 10.42 1 52 0 1
#> 136.2 21.83 1 43 0 1
#> 36 21.19 1 48 0 1
#> 56 12.21 1 60 0 0
#> 187.1 9.92 1 39 1 0
#> 162 24.00 0 51 0 0
#> 146 24.00 0 63 1 0
#> 71 24.00 0 51 0 0
#> 22 24.00 0 52 1 0
#> 47 24.00 0 38 0 1
#> 142 24.00 0 53 0 0
#> 2 24.00 0 9 0 0
#> 12 24.00 0 63 0 0
#> 21 24.00 0 47 0 0
#> 74 24.00 0 43 0 1
#> 185 24.00 0 44 1 0
#> 46 24.00 0 71 0 0
#> 19 24.00 0 57 0 1
#> 138 24.00 0 44 1 0
#> 141 24.00 0 44 1 0
#> 191 24.00 0 60 0 1
#> 191.1 24.00 0 60 0 1
#> 2.1 24.00 0 9 0 0
#> 67 24.00 0 25 0 0
#> 151 24.00 0 42 0 0
#> 191.2 24.00 0 60 0 1
#> 119 24.00 0 17 0 0
#> 62 24.00 0 71 0 0
#> 161 24.00 0 45 0 0
#> 73 24.00 0 NA 0 1
#> 87 24.00 0 27 0 0
#> 116 24.00 0 58 0 1
#> 132 24.00 0 55 0 0
#> 185.1 24.00 0 44 1 0
#> 12.1 24.00 0 63 0 0
#> 121 24.00 0 57 1 0
#> 35 24.00 0 51 0 0
#> 165 24.00 0 47 0 0
#> 144 24.00 0 28 0 1
#> 53 24.00 0 32 0 1
#> 46.1 24.00 0 71 0 0
#> 172 24.00 0 41 0 0
#> 200 24.00 0 64 0 0
#> 47.1 24.00 0 38 0 1
#> 109 24.00 0 48 0 0
#> 109.1 24.00 0 48 0 0
#> 144.1 24.00 0 28 0 1
#> 2.2 24.00 0 9 0 0
#> 72 24.00 0 40 0 1
#> 161.1 24.00 0 45 0 0
#> 147 24.00 0 76 1 0
#> 176 24.00 0 43 0 1
#> 116.1 24.00 0 58 0 1
#> 138.1 24.00 0 44 1 0
#> 160 24.00 0 31 1 0
#> 112 24.00 0 61 0 0
#> 141.1 24.00 0 44 1 0
#> 34 24.00 0 36 0 0
#> 38 24.00 0 31 1 0
#> 191.3 24.00 0 60 0 1
#> 141.2 24.00 0 44 1 0
#> 148 24.00 0 61 1 0
#> 121.1 24.00 0 57 1 0
#> 147.1 24.00 0 76 1 0
#> 35.1 24.00 0 51 0 0
#> 191.4 24.00 0 60 0 1
#> 137 24.00 0 45 1 0
#> 75 24.00 0 21 1 0
#> 98 24.00 0 34 1 0
#> 65 24.00 0 57 1 0
#> 67.1 24.00 0 25 0 0
#> 31 24.00 0 36 0 1
#> 75.1 24.00 0 21 1 0
#> 83 24.00 0 6 0 0
#> 95 24.00 0 68 0 1
#> 71.1 24.00 0 51 0 0
#> 152 24.00 0 36 0 1
#> 80 24.00 0 41 0 0
#> 67.2 24.00 0 25 0 0
#> 193 24.00 0 45 0 1
#> 87.1 24.00 0 27 0 0
#> 54 24.00 0 53 1 0
#> 62.1 24.00 0 71 0 0
#> 38.1 24.00 0 31 1 0
#> 148.1 24.00 0 61 1 0
#> 182 24.00 0 35 0 0
#> 94 24.00 0 51 0 1
#> 1 24.00 0 23 1 0
#> 27 24.00 0 63 1 0
#> 196 24.00 0 19 0 0
#> 48 24.00 0 31 1 0
#> 48.1 24.00 0 31 1 0
#> 176.1 24.00 0 43 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.805 NA NA NA
#> 2 age, Cure model 0.0147 NA NA NA
#> 3 grade_ii, Cure model 0.196 NA NA NA
#> 4 grade_iii, Cure model 0.700 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0131 NA NA NA
#> 2 grade_ii, Survival model 0.0610 NA NA NA
#> 3 grade_iii, Survival model 0.0864 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.80455 0.01468 0.19572 0.70038
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 262
#> Residual Deviance: 254.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.80454871 0.01467708 0.19572147 0.70037923
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01307040 0.06103614 0.08635746
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.5362556329 0.9167160049 0.4480446796 0.4238167428 0.2346268374
#> [6] 0.0505283912 0.1077550235 0.9003874379 0.5754014309 0.3891472856
#> [11] 0.0106872694 0.0338196442 0.2003119796 0.2628335289 0.4975401859
#> [16] 0.0298429226 0.1915464511 0.0061326274 0.0020951822 0.2003119796
#> [21] 0.3891472856 0.0020951822 0.6160000765 0.6577019842 0.0768432674
#> [26] 0.5754014309 0.1663568999 0.7599295755 0.6298179451 0.9167160049
#> [31] 0.6577019842 0.0020951822 0.6022908168 0.6437237202 0.7151086648
#> [36] 0.1429099509 0.3891472856 0.2003119796 0.0505283912 0.5103887323
#> [41] 0.0164093607 0.1011071382 0.0226130778 0.0458489009 0.1429099509
#> [46] 0.3019863900 0.3442857282 0.0603851655 0.5362556329 0.6861078767
#> [51] 0.3019863900 0.0885081032 0.0005963820 0.9167160049 0.4358392081
#> [56] 0.0005963820 0.2628335289 0.0106872694 0.8054818021 0.8523914910
#> [61] 0.4480446796 0.2917772688 0.0164093607 0.1077550235 0.7599295755
#> [66] 0.1429099509 0.0338196442 0.0768432674 0.3664383152 0.1281517165
#> [71] 0.9663160022 0.7599295755 0.3552835152 0.2532585612 0.9663160022
#> [76] 0.1829268480 0.0261148363 0.8054818021 0.3334137050 0.1077550235
#> [81] 0.1281517165 0.7448316936 0.1663568999 0.6861078767 0.5362556329
#> [86] 0.0001031987 0.2628335289 0.0947099726 0.8683472402 0.2003119796
#> [91] 0.5103887323 0.4480446796 0.0061326274 0.3226954016 0.3777287413
#> [96] 0.0603851655 0.2438730389 0.4848421578 0.8365682924 0.0338196442
#> [101] 0.0710861045 0.7298879436 0.8683472402 0.0000000000 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#>
#> $Time
#> 96 16 6 188 134 139 166 183 57 79 129 136 40
#> 14.54 8.71 15.64 16.16 17.81 21.49 19.98 9.24 14.46 16.23 23.41 21.83 18.00
#> 111 157 66 41 164 168 40.1 79.1 168.1 60 177 32 57.1
#> 17.45 15.10 22.13 18.02 23.60 23.72 18.00 16.23 23.72 13.15 12.53 20.90 14.46
#> 8 159 155 16.1 177.1 168.2 81 14 42 97 79.2 40.2 139.1
#> 18.43 10.55 13.08 8.71 12.53 23.72 14.06 12.89 12.43 19.14 16.23 18.00 21.49
#> 180 69 158 63 197 97.1 45 171 153 96.1 37 45.1 190
#> 14.82 23.23 20.14 22.77 21.60 19.14 17.42 16.57 21.33 14.54 12.52 17.42 20.81
#> 86 16.2 100 86.1 111.1 129.1 10 93 6.1 30 69.1 166.1 159.1
#> 23.81 8.71 16.07 23.81 17.45 23.41 10.53 10.33 15.64 17.43 23.23 19.98 10.55
#> 97.2 136.1 32.1 181 58 70 159.2 130 110 70.1 108 169 10.1
#> 19.14 21.83 20.90 16.46 19.34 7.38 10.55 16.47 17.56 7.38 18.29 22.41 10.53
#> 106 166.2 55 43 8.1 37.1 96.2 78 111.2 150 187 40.3 180.1
#> 16.67 19.98 19.34 12.10 18.43 12.52 14.54 23.88 17.45 20.33 9.92 18.00 14.82
#> 6.2 164.1 23 85 153.1 184 39 52 136.2 36 56 187.1 162
#> 15.64 23.60 16.92 16.44 21.33 17.77 15.59 10.42 21.83 21.19 12.21 9.92 24.00
#> 146 71 22 47 142 2 12 21 74 185 46 19 138
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 141 191 191.1 2.1 67 151 191.2 119 62 161 87 116 132
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185.1 12.1 121 35 165 144 53 46.1 172 200 47.1 109 109.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 144.1 2.2 72 161.1 147 176 116.1 138.1 160 112 141.1 34 38
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 191.3 141.2 148 121.1 147.1 35.1 191.4 137 75 98 65 67.1 31
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75.1 83 95 71.1 152 80 67.2 193 87.1 54 62.1 38.1 148.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 182 94 1 27 196 48 48.1 176.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[61]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.005349074 -0.005801586 0.381608227
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.148183693 0.002358278 -0.028698697
#> grade_iii, Cure model
#> 0.578664931
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 155 13.08 1 26 0 0
#> 158 20.14 1 74 1 0
#> 170 19.54 1 43 0 1
#> 63 22.77 1 31 1 0
#> 58 19.34 1 39 0 0
#> 184 17.77 1 38 0 0
#> 127 3.53 1 62 0 1
#> 50 10.02 1 NA 1 0
#> 108 18.29 1 39 0 1
#> 90 20.94 1 50 0 1
#> 26 15.77 1 49 0 1
#> 97 19.14 1 65 0 1
#> 76 19.22 1 54 0 1
#> 189 10.51 1 NA 1 0
#> 68 20.62 1 44 0 0
#> 157 15.10 1 47 0 0
#> 188 16.16 1 46 0 1
#> 60 13.15 1 38 1 0
#> 195 11.76 1 NA 1 0
#> 128 20.35 1 35 0 1
#> 150 20.33 1 48 0 0
#> 194 22.40 1 38 0 1
#> 76.1 19.22 1 54 0 1
#> 23 16.92 1 61 0 0
#> 190 20.81 1 42 1 0
#> 61 10.12 1 36 0 1
#> 169 22.41 1 46 0 0
#> 68.1 20.62 1 44 0 0
#> 145 10.07 1 65 1 0
#> 153 21.33 1 55 1 0
#> 188.1 16.16 1 46 0 1
#> 149 8.37 1 33 1 0
#> 57 14.46 1 45 0 1
#> 170.1 19.54 1 43 0 1
#> 76.2 19.22 1 54 0 1
#> 166 19.98 1 48 0 0
#> 63.1 22.77 1 31 1 0
#> 18 15.21 1 49 1 0
#> 136 21.83 1 43 0 1
#> 36 21.19 1 48 0 1
#> 13 14.34 1 54 0 1
#> 76.3 19.22 1 54 0 1
#> 81 14.06 1 34 0 0
#> 4 17.64 1 NA 0 1
#> 89 11.44 1 NA 0 0
#> 88 18.37 1 47 0 0
#> 79 16.23 1 54 1 0
#> 30 17.43 1 78 0 0
#> 199 19.81 1 NA 0 1
#> 86 23.81 1 58 0 1
#> 129 23.41 1 53 1 0
#> 124 9.73 1 NA 1 0
#> 37 12.52 1 57 1 0
#> 63.2 22.77 1 31 1 0
#> 169.1 22.41 1 46 0 0
#> 159 10.55 1 50 0 1
#> 153.1 21.33 1 55 1 0
#> 58.1 19.34 1 39 0 0
#> 69 23.23 1 25 0 1
#> 184.1 17.77 1 38 0 0
#> 101 9.97 1 10 0 1
#> 130 16.47 1 53 0 1
#> 155.1 13.08 1 26 0 0
#> 139 21.49 1 63 1 0
#> 81.1 14.06 1 34 0 0
#> 90.1 20.94 1 50 0 1
#> 40 18.00 1 28 1 0
#> 43 12.10 1 61 0 1
#> 108.1 18.29 1 39 0 1
#> 192 16.44 1 31 1 0
#> 39 15.59 1 37 0 1
#> 101.1 9.97 1 10 0 1
#> 45 17.42 1 54 0 1
#> 167 15.55 1 56 1 0
#> 96 14.54 1 33 0 1
#> 76.4 19.22 1 54 0 1
#> 169.2 22.41 1 46 0 0
#> 150.1 20.33 1 48 0 0
#> 4.1 17.64 1 NA 0 1
#> 111 17.45 1 47 0 1
#> 26.1 15.77 1 49 0 1
#> 113 22.86 1 34 0 0
#> 105 19.75 1 60 0 0
#> 32 20.90 1 37 1 0
#> 180 14.82 1 37 0 0
#> 153.2 21.33 1 55 1 0
#> 125 15.65 1 67 1 0
#> 188.2 16.16 1 46 0 1
#> 124.1 9.73 1 NA 1 0
#> 61.1 10.12 1 36 0 1
#> 78 23.88 1 43 0 0
#> 129.1 23.41 1 53 1 0
#> 197 21.60 1 69 1 0
#> 61.2 10.12 1 36 0 1
#> 199.1 19.81 1 NA 0 1
#> 195.1 11.76 1 NA 1 0
#> 32.1 20.90 1 37 1 0
#> 199.2 19.81 1 NA 0 1
#> 175 21.91 1 43 0 0
#> 25 6.32 1 34 1 0
#> 189.1 10.51 1 NA 1 0
#> 177 12.53 1 75 0 0
#> 81.2 14.06 1 34 0 0
#> 123 13.00 1 44 1 0
#> 24 23.89 1 38 0 0
#> 77 7.27 1 67 0 1
#> 56 12.21 1 60 0 0
#> 29 15.45 1 68 1 0
#> 190.1 20.81 1 42 1 0
#> 158.1 20.14 1 74 1 0
#> 92 22.92 1 47 0 1
#> 91 5.33 1 61 0 1
#> 160 24.00 0 31 1 0
#> 178 24.00 0 52 1 0
#> 82 24.00 0 34 0 0
#> 148 24.00 0 61 1 0
#> 142 24.00 0 53 0 0
#> 172 24.00 0 41 0 0
#> 33 24.00 0 53 0 0
#> 54 24.00 0 53 1 0
#> 131 24.00 0 66 0 0
#> 35 24.00 0 51 0 0
#> 48 24.00 0 31 1 0
#> 75 24.00 0 21 1 0
#> 173 24.00 0 19 0 1
#> 144 24.00 0 28 0 1
#> 53 24.00 0 32 0 1
#> 178.1 24.00 0 52 1 0
#> 121 24.00 0 57 1 0
#> 75.1 24.00 0 21 1 0
#> 48.1 24.00 0 31 1 0
#> 34 24.00 0 36 0 0
#> 193 24.00 0 45 0 1
#> 65 24.00 0 57 1 0
#> 160.1 24.00 0 31 1 0
#> 12 24.00 0 63 0 0
#> 94 24.00 0 51 0 1
#> 185 24.00 0 44 1 0
#> 28 24.00 0 67 1 0
#> 116 24.00 0 58 0 1
#> 33.1 24.00 0 53 0 0
#> 102 24.00 0 49 0 0
#> 146 24.00 0 63 1 0
#> 156 24.00 0 50 1 0
#> 120 24.00 0 68 0 1
#> 19 24.00 0 57 0 1
#> 186 24.00 0 45 1 0
#> 151 24.00 0 42 0 0
#> 173.1 24.00 0 19 0 1
#> 62 24.00 0 71 0 0
#> 161 24.00 0 45 0 0
#> 54.1 24.00 0 53 1 0
#> 132 24.00 0 55 0 0
#> 46 24.00 0 71 0 0
#> 28.1 24.00 0 67 1 0
#> 182 24.00 0 35 0 0
#> 47 24.00 0 38 0 1
#> 186.1 24.00 0 45 1 0
#> 176 24.00 0 43 0 1
#> 173.2 24.00 0 19 0 1
#> 172.1 24.00 0 41 0 0
#> 9 24.00 0 31 1 0
#> 75.2 24.00 0 21 1 0
#> 73 24.00 0 NA 0 1
#> 162 24.00 0 51 0 0
#> 22 24.00 0 52 1 0
#> 135 24.00 0 58 1 0
#> 173.3 24.00 0 19 0 1
#> 116.1 24.00 0 58 0 1
#> 75.3 24.00 0 21 1 0
#> 20 24.00 0 46 1 0
#> 109 24.00 0 48 0 0
#> 200 24.00 0 64 0 0
#> 165 24.00 0 47 0 0
#> 148.1 24.00 0 61 1 0
#> 75.4 24.00 0 21 1 0
#> 115 24.00 0 NA 1 0
#> 176.1 24.00 0 43 0 1
#> 173.4 24.00 0 19 0 1
#> 95 24.00 0 68 0 1
#> 162.1 24.00 0 51 0 0
#> 103 24.00 0 56 1 0
#> 132.1 24.00 0 55 0 0
#> 98 24.00 0 34 1 0
#> 102.1 24.00 0 49 0 0
#> 80 24.00 0 41 0 0
#> 112 24.00 0 61 0 0
#> 198 24.00 0 66 0 1
#> 198.1 24.00 0 66 0 1
#> 163 24.00 0 66 0 0
#> 47.1 24.00 0 38 0 1
#> 53.1 24.00 0 32 0 1
#> 73.1 24.00 0 NA 0 1
#> 152 24.00 0 36 0 1
#> 138 24.00 0 44 1 0
#> 193.1 24.00 0 45 0 1
#> 12.1 24.00 0 63 0 0
#> 44 24.00 0 56 0 0
#> 165.1 24.00 0 47 0 0
#> 94.1 24.00 0 51 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.148 NA NA NA
#> 2 age, Cure model 0.00236 NA NA NA
#> 3 grade_ii, Cure model -0.0287 NA NA NA
#> 4 grade_iii, Cure model 0.579 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00535 NA NA NA
#> 2 grade_ii, Survival model -0.00580 NA NA NA
#> 3 grade_iii, Survival model 0.382 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.148184 0.002358 -0.028699 0.578665
#>
#> Degrees of Freedom: 183 Total (i.e. Null); 180 Residual
#> Null Deviance: 254
#> Residual Deviance: 250.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.148183693 0.002358278 -0.028698697 0.578664931
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.005349074 -0.005801586 0.381608227
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.86982680 0.49575460 0.53507679 0.19168695 0.55391740 0.65711615
#> [7] 0.99341985 0.63212862 0.38145514 0.75274112 0.61498606 0.57261060
#> [13] 0.44484305 0.80496402 0.72991300 0.86269017 0.46546701 0.47571983
#> [19] 0.27222711 0.57261060 0.69807804 0.42396241 0.92619279 0.23291640
#> [25] 0.44484305 0.94648412 0.33585572 0.72991300 0.96671003 0.82698395
#> [31] 0.53507679 0.57261060 0.51541060 0.19168695 0.79757868 0.29858368
#> [37] 0.37002143 0.83423120 0.57261060 0.84141880 0.62357417 0.72200464
#> [43] 0.68183977 0.08651932 0.10814911 0.89818704 0.19168695 0.23291640
#> [49] 0.91926034 0.33585572 0.55391740 0.14321494 0.65711615 0.95327688
#> [55] 0.70611569 0.86982680 0.32362793 0.84141880 0.38145514 0.64876210
#> [61] 0.91227978 0.63212862 0.71406783 0.77527840 0.95327688 0.69000453
#> [67] 0.78273795 0.81968147 0.57261060 0.23291640 0.47571983 0.67362408
#> [73] 0.75274112 0.17621029 0.52527852 0.40282737 0.81233004 0.33585572
#> [79] 0.76776207 0.72991300 0.92619279 0.05784649 0.10814911 0.31121610
#> [85] 0.92619279 0.40282737 0.28548399 0.98012208 0.89111091 0.84141880
#> [91] 0.88400694 0.02557795 0.97344137 0.90524379 0.79017331 0.42396241
#> [97] 0.49575460 0.16045879 0.98679403 0.00000000 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 155 158 170 63 58 184 127 108 90 26 97 76 68
#> 13.08 20.14 19.54 22.77 19.34 17.77 3.53 18.29 20.94 15.77 19.14 19.22 20.62
#> 157 188 60 128 150 194 76.1 23 190 61 169 68.1 145
#> 15.10 16.16 13.15 20.35 20.33 22.40 19.22 16.92 20.81 10.12 22.41 20.62 10.07
#> 153 188.1 149 57 170.1 76.2 166 63.1 18 136 36 13 76.3
#> 21.33 16.16 8.37 14.46 19.54 19.22 19.98 22.77 15.21 21.83 21.19 14.34 19.22
#> 81 88 79 30 86 129 37 63.2 169.1 159 153.1 58.1 69
#> 14.06 18.37 16.23 17.43 23.81 23.41 12.52 22.77 22.41 10.55 21.33 19.34 23.23
#> 184.1 101 130 155.1 139 81.1 90.1 40 43 108.1 192 39 101.1
#> 17.77 9.97 16.47 13.08 21.49 14.06 20.94 18.00 12.10 18.29 16.44 15.59 9.97
#> 45 167 96 76.4 169.2 150.1 111 26.1 113 105 32 180 153.2
#> 17.42 15.55 14.54 19.22 22.41 20.33 17.45 15.77 22.86 19.75 20.90 14.82 21.33
#> 125 188.2 61.1 78 129.1 197 61.2 32.1 175 25 177 81.2 123
#> 15.65 16.16 10.12 23.88 23.41 21.60 10.12 20.90 21.91 6.32 12.53 14.06 13.00
#> 24 77 56 29 190.1 158.1 92 91 160 178 82 148 142
#> 23.89 7.27 12.21 15.45 20.81 20.14 22.92 5.33 24.00 24.00 24.00 24.00 24.00
#> 172 33 54 131 35 48 75 173 144 53 178.1 121 75.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 48.1 34 193 65 160.1 12 94 185 28 116 33.1 102 146
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156 120 19 186 151 173.1 62 161 54.1 132 46 28.1 182
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 47 186.1 176 173.2 172.1 9 75.2 162 22 135 173.3 116.1 75.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20 109 200 165 148.1 75.4 176.1 173.4 95 162.1 103 132.1 98
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 102.1 80 112 198 198.1 163 47.1 53.1 152 138 193.1 12.1 44
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165.1 94.1
#> 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[62]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01331836 1.28974606 0.36906628
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.57901119 -0.01109750 -0.09775587
#> grade_iii, Cure model
#> 0.45515000
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 52 10.42 1 52 0 1
#> 154 12.63 1 20 1 0
#> 150 20.33 1 48 0 0
#> 32 20.90 1 37 1 0
#> 149 8.37 1 33 1 0
#> 97 19.14 1 65 0 1
#> 37 12.52 1 57 1 0
#> 45 17.42 1 54 0 1
#> 86 23.81 1 58 0 1
#> 155 13.08 1 26 0 0
#> 81 14.06 1 34 0 0
#> 154.1 12.63 1 20 1 0
#> 79 16.23 1 54 1 0
#> 61 10.12 1 36 0 1
#> 97.1 19.14 1 65 0 1
#> 40 18.00 1 28 1 0
#> 136 21.83 1 43 0 1
#> 149.1 8.37 1 33 1 0
#> 14 12.89 1 21 0 0
#> 184 17.77 1 38 0 0
#> 8 18.43 1 32 0 0
#> 49 12.19 1 48 1 0
#> 8.1 18.43 1 32 0 0
#> 171 16.57 1 41 0 1
#> 86.1 23.81 1 58 0 1
#> 113 22.86 1 34 0 0
#> 5 16.43 1 51 0 1
#> 195 11.76 1 NA 1 0
#> 110 17.56 1 65 0 1
#> 69 23.23 1 25 0 1
#> 37.1 12.52 1 57 1 0
#> 97.2 19.14 1 65 0 1
#> 169 22.41 1 46 0 0
#> 56 12.21 1 60 0 0
#> 81.1 14.06 1 34 0 0
#> 50 10.02 1 NA 1 0
#> 66 22.13 1 53 0 0
#> 136.1 21.83 1 43 0 1
#> 89 11.44 1 NA 0 0
#> 30 17.43 1 78 0 0
#> 55 19.34 1 69 0 1
#> 37.2 12.52 1 57 1 0
#> 184.1 17.77 1 38 0 0
#> 24 23.89 1 38 0 0
#> 168 23.72 1 70 0 0
#> 55.1 19.34 1 69 0 1
#> 23 16.92 1 61 0 0
#> 114 13.68 1 NA 0 0
#> 108 18.29 1 39 0 1
#> 59 10.16 1 NA 1 0
#> 133 14.65 1 57 0 0
#> 139 21.49 1 63 1 0
#> 76 19.22 1 54 0 1
#> 60 13.15 1 38 1 0
#> 128 20.35 1 35 0 1
#> 105 19.75 1 60 0 0
#> 192 16.44 1 31 1 0
#> 40.1 18.00 1 28 1 0
#> 49.1 12.19 1 48 1 0
#> 100 16.07 1 60 0 0
#> 187 9.92 1 39 1 0
#> 59.1 10.16 1 NA 1 0
#> 150.1 20.33 1 48 0 0
#> 24.1 23.89 1 38 0 0
#> 159 10.55 1 50 0 1
#> 90 20.94 1 50 0 1
#> 167 15.55 1 56 1 0
#> 113.1 22.86 1 34 0 0
#> 114.1 13.68 1 NA 0 0
#> 164 23.60 1 76 0 1
#> 15 22.68 1 48 0 0
#> 4 17.64 1 NA 0 1
#> 55.2 19.34 1 69 0 1
#> 194 22.40 1 38 0 1
#> 183 9.24 1 67 1 0
#> 70 7.38 1 30 1 0
#> 79.1 16.23 1 54 1 0
#> 125 15.65 1 67 1 0
#> 58 19.34 1 39 0 0
#> 99 21.19 1 38 0 1
#> 124 9.73 1 NA 1 0
#> 169.1 22.41 1 46 0 0
#> 114.2 13.68 1 NA 0 0
#> 167.1 15.55 1 56 1 0
#> 51 18.23 1 83 0 1
#> 155.1 13.08 1 26 0 0
#> 150.2 20.33 1 48 0 0
#> 123 13.00 1 44 1 0
#> 37.3 12.52 1 57 1 0
#> 199 19.81 1 NA 0 1
#> 139.1 21.49 1 63 1 0
#> 153 21.33 1 55 1 0
#> 175 21.91 1 43 0 0
#> 88 18.37 1 47 0 0
#> 25 6.32 1 34 1 0
#> 171.1 16.57 1 41 0 1
#> 88.1 18.37 1 47 0 0
#> 117 17.46 1 26 0 1
#> 184.2 17.77 1 38 0 0
#> 24.2 23.89 1 38 0 0
#> 158 20.14 1 74 1 0
#> 57 14.46 1 45 0 1
#> 155.2 13.08 1 26 0 0
#> 140 12.68 1 59 1 0
#> 149.2 8.37 1 33 1 0
#> 42 12.43 1 49 0 1
#> 111 17.45 1 47 0 1
#> 159.1 10.55 1 50 0 1
#> 101 9.97 1 10 0 1
#> 155.3 13.08 1 26 0 0
#> 170 19.54 1 43 0 1
#> 66.1 22.13 1 53 0 0
#> 147 24.00 0 76 1 0
#> 156 24.00 0 50 1 0
#> 87 24.00 0 27 0 0
#> 162 24.00 0 51 0 0
#> 11 24.00 0 42 0 1
#> 163 24.00 0 66 0 0
#> 84 24.00 0 39 0 1
#> 161 24.00 0 45 0 0
#> 160 24.00 0 31 1 0
#> 156.1 24.00 0 50 1 0
#> 72 24.00 0 40 0 1
#> 160.1 24.00 0 31 1 0
#> 109 24.00 0 48 0 0
#> 131 24.00 0 66 0 0
#> 20 24.00 0 46 1 0
#> 102 24.00 0 49 0 0
#> 46 24.00 0 71 0 0
#> 148 24.00 0 61 1 0
#> 176 24.00 0 43 0 1
#> 73 24.00 0 NA 0 1
#> 143 24.00 0 51 0 0
#> 22 24.00 0 52 1 0
#> 132 24.00 0 55 0 0
#> 75 24.00 0 21 1 0
#> 198 24.00 0 66 0 1
#> 151 24.00 0 42 0 0
#> 186 24.00 0 45 1 0
#> 122 24.00 0 66 0 0
#> 116 24.00 0 58 0 1
#> 94 24.00 0 51 0 1
#> 102.1 24.00 0 49 0 0
#> 109.1 24.00 0 48 0 0
#> 163.1 24.00 0 66 0 0
#> 31 24.00 0 36 0 1
#> 200 24.00 0 64 0 0
#> 151.1 24.00 0 42 0 0
#> 198.1 24.00 0 66 0 1
#> 22.1 24.00 0 52 1 0
#> 95 24.00 0 68 0 1
#> 95.1 24.00 0 68 0 1
#> 176.1 24.00 0 43 0 1
#> 21 24.00 0 47 0 0
#> 54 24.00 0 53 1 0
#> 144 24.00 0 28 0 1
#> 112 24.00 0 61 0 0
#> 173 24.00 0 19 0 1
#> 54.1 24.00 0 53 1 0
#> 132.1 24.00 0 55 0 0
#> 132.2 24.00 0 55 0 0
#> 72.1 24.00 0 40 0 1
#> 122.1 24.00 0 66 0 0
#> 38 24.00 0 31 1 0
#> 156.2 24.00 0 50 1 0
#> 178 24.00 0 52 1 0
#> 20.1 24.00 0 46 1 0
#> 75.1 24.00 0 21 1 0
#> 138 24.00 0 44 1 0
#> 116.1 24.00 0 58 0 1
#> 132.3 24.00 0 55 0 0
#> 72.2 24.00 0 40 0 1
#> 19 24.00 0 57 0 1
#> 178.1 24.00 0 52 1 0
#> 54.2 24.00 0 53 1 0
#> 185 24.00 0 44 1 0
#> 148.1 24.00 0 61 1 0
#> 112.1 24.00 0 61 0 0
#> 186.1 24.00 0 45 1 0
#> 2 24.00 0 9 0 0
#> 161.1 24.00 0 45 0 0
#> 19.1 24.00 0 57 0 1
#> 137 24.00 0 45 1 0
#> 165 24.00 0 47 0 0
#> 67 24.00 0 25 0 0
#> 38.1 24.00 0 31 1 0
#> 65 24.00 0 57 1 0
#> 148.2 24.00 0 61 1 0
#> 33 24.00 0 53 0 0
#> 74 24.00 0 43 0 1
#> 156.3 24.00 0 50 1 0
#> 38.2 24.00 0 31 1 0
#> 116.2 24.00 0 58 0 1
#> 121 24.00 0 57 1 0
#> 162.1 24.00 0 51 0 0
#> 119 24.00 0 17 0 0
#> 12 24.00 0 63 0 0
#> 75.2 24.00 0 21 1 0
#> 12.1 24.00 0 63 0 0
#> 161.2 24.00 0 45 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.579 NA NA NA
#> 2 age, Cure model -0.0111 NA NA NA
#> 3 grade_ii, Cure model -0.0978 NA NA NA
#> 4 grade_iii, Cure model 0.455 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0133 NA NA NA
#> 2 grade_ii, Survival model 1.29 NA NA NA
#> 3 grade_iii, Survival model 0.369 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.57901 -0.01110 -0.09776 0.45515
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 259.6
#> Residual Deviance: 256.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.57901119 -0.01109750 -0.09775587 0.45515000
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01331836 1.28974606 0.36906628
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.903512619 0.783202197 0.204967586 0.186516145 0.953375893 0.313433715
#> [7] 0.803963816 0.514318041 0.009768388 0.706292875 0.673003998 0.783202197
#> [13] 0.584277495 0.913552861 0.313433715 0.414292393 0.116907824 0.953375893
#> [19] 0.761154121 0.435841574 0.345581447 0.863810958 0.345581447 0.537726613
#> [25] 0.009768388 0.038088085 0.572701278 0.468719455 0.031307243 0.803963816
#> [31] 0.313433715 0.060260981 0.853642064 0.673003998 0.086670275 0.116907824
#> [37] 0.502763394 0.262726596 0.803963816 0.435841574 0.001859571 0.018451727
#> [43] 0.262726596 0.525949891 0.390758639 0.650851289 0.138036313 0.302773472
#> [49] 0.695277197 0.195721713 0.242873765 0.561187134 0.414292393 0.863810958
#> [55] 0.606529205 0.933627424 0.204967586 0.001859571 0.883604510 0.176721627
#> [61] 0.629119270 0.038088085 0.024478168 0.052130889 0.262726596 0.077415772
#> [67] 0.943526870 0.981464262 0.584277495 0.617874610 0.262726596 0.167064679
#> [73] 0.060260981 0.629119270 0.402435864 0.706292875 0.204967586 0.750117708
#> [79] 0.803963816 0.138036313 0.157478820 0.106197231 0.367847313 0.990788879
#> [85] 0.537726613 0.367847313 0.480051713 0.435841574 0.001859571 0.233200074
#> [91] 0.661908581 0.706292875 0.772229717 0.953375893 0.843539393 0.491377822
#> [97] 0.883604510 0.923604651 0.706292875 0.252764252 0.086670275 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000
#>
#> $Time
#> 52 154 150 32 149 97 37 45 86 155 81 154.1 79
#> 10.42 12.63 20.33 20.90 8.37 19.14 12.52 17.42 23.81 13.08 14.06 12.63 16.23
#> 61 97.1 40 136 149.1 14 184 8 49 8.1 171 86.1 113
#> 10.12 19.14 18.00 21.83 8.37 12.89 17.77 18.43 12.19 18.43 16.57 23.81 22.86
#> 5 110 69 37.1 97.2 169 56 81.1 66 136.1 30 55 37.2
#> 16.43 17.56 23.23 12.52 19.14 22.41 12.21 14.06 22.13 21.83 17.43 19.34 12.52
#> 184.1 24 168 55.1 23 108 133 139 76 60 128 105 192
#> 17.77 23.89 23.72 19.34 16.92 18.29 14.65 21.49 19.22 13.15 20.35 19.75 16.44
#> 40.1 49.1 100 187 150.1 24.1 159 90 167 113.1 164 15 55.2
#> 18.00 12.19 16.07 9.92 20.33 23.89 10.55 20.94 15.55 22.86 23.60 22.68 19.34
#> 194 183 70 79.1 125 58 99 169.1 167.1 51 155.1 150.2 123
#> 22.40 9.24 7.38 16.23 15.65 19.34 21.19 22.41 15.55 18.23 13.08 20.33 13.00
#> 37.3 139.1 153 175 88 25 171.1 88.1 117 184.2 24.2 158 57
#> 12.52 21.49 21.33 21.91 18.37 6.32 16.57 18.37 17.46 17.77 23.89 20.14 14.46
#> 155.2 140 149.2 42 111 159.1 101 155.3 170 66.1 147 156 87
#> 13.08 12.68 8.37 12.43 17.45 10.55 9.97 13.08 19.54 22.13 24.00 24.00 24.00
#> 162 11 163 84 161 160 156.1 72 160.1 109 131 20 102
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 46 148 176 143 22 132 75 198 151 186 122 116 94
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 102.1 109.1 163.1 31 200 151.1 198.1 22.1 95 95.1 176.1 21 54
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 144 112 173 54.1 132.1 132.2 72.1 122.1 38 156.2 178 20.1 75.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 138 116.1 132.3 72.2 19 178.1 54.2 185 148.1 112.1 186.1 2 161.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 19.1 137 165 67 38.1 65 148.2 33 74 156.3 38.2 116.2 121
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 162.1 119 12 75.2 12.1 161.2
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[63]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.004150864 0.476562120 0.502013773
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.91992738 0.01961530 -0.02878136
#> grade_iii, Cure model
#> 0.60886571
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 57 14.46 1 45 0 1
#> 124 9.73 1 NA 1 0
#> 150 20.33 1 48 0 0
#> 180 14.82 1 37 0 0
#> 164 23.60 1 76 0 1
#> 175 21.91 1 43 0 0
#> 4 17.64 1 NA 0 1
#> 123 13.00 1 44 1 0
#> 113 22.86 1 34 0 0
#> 70 7.38 1 30 1 0
#> 99 21.19 1 38 0 1
#> 140 12.68 1 59 1 0
#> 150.1 20.33 1 48 0 0
#> 107 11.18 1 54 1 0
#> 123.1 13.00 1 44 1 0
#> 197 21.60 1 69 1 0
#> 16 8.71 1 71 0 1
#> 30 17.43 1 78 0 0
#> 177 12.53 1 75 0 0
#> 42 12.43 1 49 0 1
#> 32 20.90 1 37 1 0
#> 69 23.23 1 25 0 1
#> 129 23.41 1 53 1 0
#> 188 16.16 1 46 0 1
#> 10 10.53 1 34 0 0
#> 26 15.77 1 49 0 1
#> 134 17.81 1 47 1 0
#> 26.1 15.77 1 49 0 1
#> 45 17.42 1 54 0 1
#> 14 12.89 1 21 0 0
#> 189 10.51 1 NA 1 0
#> 105 19.75 1 60 0 0
#> 8 18.43 1 32 0 0
#> 18 15.21 1 49 1 0
#> 4.1 17.64 1 NA 0 1
#> 18.1 15.21 1 49 1 0
#> 192 16.44 1 31 1 0
#> 129.1 23.41 1 53 1 0
#> 110 17.56 1 65 0 1
#> 24 23.89 1 38 0 0
#> 123.2 13.00 1 44 1 0
#> 52 10.42 1 52 0 1
#> 92 22.92 1 47 0 1
#> 5 16.43 1 51 0 1
#> 101 9.97 1 10 0 1
#> 105.1 19.75 1 60 0 0
#> 183 9.24 1 67 1 0
#> 43 12.10 1 61 0 1
#> 58 19.34 1 39 0 0
#> 26.2 15.77 1 49 0 1
#> 128 20.35 1 35 0 1
#> 10.1 10.53 1 34 0 0
#> 41 18.02 1 40 1 0
#> 99.1 21.19 1 38 0 1
#> 110.1 17.56 1 65 0 1
#> 66 22.13 1 53 0 0
#> 68 20.62 1 44 0 0
#> 139 21.49 1 63 1 0
#> 79 16.23 1 54 1 0
#> 50 10.02 1 NA 1 0
#> 175.1 21.91 1 43 0 0
#> 59 10.16 1 NA 1 0
#> 159 10.55 1 50 0 1
#> 110.2 17.56 1 65 0 1
#> 30.1 17.43 1 78 0 0
#> 169 22.41 1 46 0 0
#> 78 23.88 1 43 0 0
#> 85 16.44 1 36 0 0
#> 110.3 17.56 1 65 0 1
#> 99.2 21.19 1 38 0 1
#> 63 22.77 1 31 1 0
#> 15 22.68 1 48 0 0
#> 188.1 16.16 1 46 0 1
#> 60 13.15 1 38 1 0
#> 76 19.22 1 54 0 1
#> 90 20.94 1 50 0 1
#> 149 8.37 1 33 1 0
#> 68.1 20.62 1 44 0 0
#> 197.1 21.60 1 69 1 0
#> 79.1 16.23 1 54 1 0
#> 50.1 10.02 1 NA 1 0
#> 58.1 19.34 1 39 0 0
#> 197.2 21.60 1 69 1 0
#> 134.1 17.81 1 47 1 0
#> 43.1 12.10 1 61 0 1
#> 32.1 20.90 1 37 1 0
#> 77 7.27 1 67 0 1
#> 85.1 16.44 1 36 0 0
#> 158 20.14 1 74 1 0
#> 129.2 23.41 1 53 1 0
#> 5.1 16.43 1 51 0 1
#> 128.1 20.35 1 35 0 1
#> 188.2 16.16 1 46 0 1
#> 181 16.46 1 45 0 1
#> 57.1 14.46 1 45 0 1
#> 169.1 22.41 1 46 0 0
#> 86 23.81 1 58 0 1
#> 157 15.10 1 47 0 0
#> 97 19.14 1 65 0 1
#> 18.2 15.21 1 49 1 0
#> 195 11.76 1 NA 1 0
#> 93 10.33 1 52 0 1
#> 157.1 15.10 1 47 0 0
#> 39 15.59 1 37 0 1
#> 36 21.19 1 48 0 1
#> 13 14.34 1 54 0 1
#> 168 23.72 1 70 0 0
#> 125 15.65 1 67 1 0
#> 29 15.45 1 68 1 0
#> 124.1 9.73 1 NA 1 0
#> 25 6.32 1 34 1 0
#> 125.1 15.65 1 67 1 0
#> 48 24.00 0 31 1 0
#> 48.1 24.00 0 31 1 0
#> 162 24.00 0 51 0 0
#> 94 24.00 0 51 0 1
#> 148 24.00 0 61 1 0
#> 156 24.00 0 50 1 0
#> 135 24.00 0 58 1 0
#> 94.1 24.00 0 51 0 1
#> 162.1 24.00 0 51 0 0
#> 94.2 24.00 0 51 0 1
#> 19 24.00 0 57 0 1
#> 172 24.00 0 41 0 0
#> 98 24.00 0 34 1 0
#> 2 24.00 0 9 0 0
#> 115 24.00 0 NA 1 0
#> 9 24.00 0 31 1 0
#> 143 24.00 0 51 0 0
#> 84 24.00 0 39 0 1
#> 84.1 24.00 0 39 0 1
#> 120 24.00 0 68 0 1
#> 12 24.00 0 63 0 0
#> 120.1 24.00 0 68 0 1
#> 67 24.00 0 25 0 0
#> 185 24.00 0 44 1 0
#> 138 24.00 0 44 1 0
#> 186 24.00 0 45 1 0
#> 72 24.00 0 40 0 1
#> 162.2 24.00 0 51 0 0
#> 75 24.00 0 21 1 0
#> 198 24.00 0 66 0 1
#> 2.1 24.00 0 9 0 0
#> 33 24.00 0 53 0 0
#> 103 24.00 0 56 1 0
#> 135.1 24.00 0 58 1 0
#> 151 24.00 0 42 0 0
#> 161 24.00 0 45 0 0
#> 80 24.00 0 41 0 0
#> 186.1 24.00 0 45 1 0
#> 72.1 24.00 0 40 0 1
#> 137 24.00 0 45 1 0
#> 22 24.00 0 52 1 0
#> 71 24.00 0 51 0 0
#> 65 24.00 0 57 1 0
#> 103.1 24.00 0 56 1 0
#> 12.1 24.00 0 63 0 0
#> 22.1 24.00 0 52 1 0
#> 119 24.00 0 17 0 0
#> 12.2 24.00 0 63 0 0
#> 28 24.00 0 67 1 0
#> 137.1 24.00 0 45 1 0
#> 198.1 24.00 0 66 0 1
#> 33.1 24.00 0 53 0 0
#> 2.2 24.00 0 9 0 0
#> 172.1 24.00 0 41 0 0
#> 34 24.00 0 36 0 0
#> 131 24.00 0 66 0 0
#> 148.1 24.00 0 61 1 0
#> 174 24.00 0 49 1 0
#> 144 24.00 0 28 0 1
#> 27 24.00 0 63 1 0
#> 1 24.00 0 23 1 0
#> 186.2 24.00 0 45 1 0
#> 9.1 24.00 0 31 1 0
#> 142 24.00 0 53 0 0
#> 119.1 24.00 0 17 0 0
#> 193 24.00 0 45 0 1
#> 200 24.00 0 64 0 0
#> 115.1 24.00 0 NA 1 0
#> 141 24.00 0 44 1 0
#> 163 24.00 0 66 0 0
#> 138.1 24.00 0 44 1 0
#> 121 24.00 0 57 1 0
#> 151.1 24.00 0 42 0 0
#> 3 24.00 0 31 1 0
#> 163.1 24.00 0 66 0 0
#> 193.1 24.00 0 45 0 1
#> 21 24.00 0 47 0 0
#> 94.3 24.00 0 51 0 1
#> 19.1 24.00 0 57 0 1
#> 152 24.00 0 36 0 1
#> 82 24.00 0 34 0 0
#> 82.1 24.00 0 34 0 0
#> 98.1 24.00 0 34 1 0
#> 152.1 24.00 0 36 0 1
#> 115.2 24.00 0 NA 1 0
#> 72.2 24.00 0 40 0 1
#> 173 24.00 0 19 0 1
#> 104 24.00 0 50 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.920 NA NA NA
#> 2 age, Cure model 0.0196 NA NA NA
#> 3 grade_ii, Cure model -0.0288 NA NA NA
#> 4 grade_iii, Cure model 0.609 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00415 NA NA NA
#> 2 grade_ii, Survival model 0.477 NA NA NA
#> 3 grade_iii, Survival model 0.502 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.91993 0.01962 -0.02878 0.60887
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 258.9
#> Residual Deviance: 251.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.91992738 0.01961530 -0.02878136 0.60886571
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.004150864 0.476562120 0.502013773
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.781124505 0.374928878 0.772373692 0.065582061 0.201837863 0.815646160
#> [7] 0.135437071 0.975356003 0.267341483 0.849467514 0.374928878 0.891811298
#> [13] 0.815646160 0.224367687 0.958798072 0.538496122 0.857970505 0.866496101
#> [19] 0.316514333 0.112820476 0.080289988 0.640687179 0.908637277 0.667489492
#> [25] 0.482645238 0.667489492 0.557378785 0.840942277 0.404123291 0.463026696
#> [31] 0.729192345 0.729192345 0.576262220 0.080289988 0.501743110 0.006164551
#> [37] 0.815646160 0.925399299 0.124313009 0.603979847 0.942162392 0.404123291
#> [43] 0.950488221 0.874992605 0.423658844 0.667489492 0.355697635 0.908637277
#> [49] 0.472873010 0.267341483 0.501743110 0.190454869 0.336010507 0.256326858
#> [55] 0.622411186 0.201837863 0.900237747 0.501743110 0.538496122 0.168619296
#> [61] 0.019879095 0.576262220 0.501743110 0.267341483 0.146683169 0.157582155
#> [67] 0.640687179 0.807033211 0.443330106 0.306369531 0.967091367 0.336010507
#> [73] 0.224367687 0.622411186 0.423658844 0.224367687 0.482645238 0.874992605
#> [79] 0.316514333 0.983591196 0.576262220 0.394340167 0.080289988 0.603979847
#> [85] 0.355697635 0.640687179 0.566849638 0.781124505 0.168619296 0.035915545
#> [91] 0.754999078 0.453206364 0.729192345 0.933793307 0.754999078 0.711559614
#> [97] 0.267341483 0.798385606 0.050184680 0.693922631 0.720387549 0.991809122
#> [103] 0.693922631 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000
#>
#> $Time
#> 57 150 180 164 175 123 113 70 99 140 150.1 107 123.1
#> 14.46 20.33 14.82 23.60 21.91 13.00 22.86 7.38 21.19 12.68 20.33 11.18 13.00
#> 197 16 30 177 42 32 69 129 188 10 26 134 26.1
#> 21.60 8.71 17.43 12.53 12.43 20.90 23.23 23.41 16.16 10.53 15.77 17.81 15.77
#> 45 14 105 8 18 18.1 192 129.1 110 24 123.2 52 92
#> 17.42 12.89 19.75 18.43 15.21 15.21 16.44 23.41 17.56 23.89 13.00 10.42 22.92
#> 5 101 105.1 183 43 58 26.2 128 10.1 41 99.1 110.1 66
#> 16.43 9.97 19.75 9.24 12.10 19.34 15.77 20.35 10.53 18.02 21.19 17.56 22.13
#> 68 139 79 175.1 159 110.2 30.1 169 78 85 110.3 99.2 63
#> 20.62 21.49 16.23 21.91 10.55 17.56 17.43 22.41 23.88 16.44 17.56 21.19 22.77
#> 15 188.1 60 76 90 149 68.1 197.1 79.1 58.1 197.2 134.1 43.1
#> 22.68 16.16 13.15 19.22 20.94 8.37 20.62 21.60 16.23 19.34 21.60 17.81 12.10
#> 32.1 77 85.1 158 129.2 5.1 128.1 188.2 181 57.1 169.1 86 157
#> 20.90 7.27 16.44 20.14 23.41 16.43 20.35 16.16 16.46 14.46 22.41 23.81 15.10
#> 97 18.2 93 157.1 39 36 13 168 125 29 25 125.1 48
#> 19.14 15.21 10.33 15.10 15.59 21.19 14.34 23.72 15.65 15.45 6.32 15.65 24.00
#> 48.1 162 94 148 156 135 94.1 162.1 94.2 19 172 98 2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9 143 84 84.1 120 12 120.1 67 185 138 186 72 162.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75 198 2.1 33 103 135.1 151 161 80 186.1 72.1 137 22
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71 65 103.1 12.1 22.1 119 12.2 28 137.1 198.1 33.1 2.2 172.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34 131 148.1 174 144 27 1 186.2 9.1 142 119.1 193 200
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 141 163 138.1 121 151.1 3 163.1 193.1 21 94.3 19.1 152 82
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 82.1 98.1 152.1 72.2 173 104
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[64]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.003246912 0.358462944 0.392066443
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.9171835 0.0143704 0.3323578
#> grade_iii, Cure model
#> 0.9342222
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 199 19.81 1 NA 0 1
#> 158 20.14 1 74 1 0
#> 101 9.97 1 10 0 1
#> 181 16.46 1 45 0 1
#> 124 9.73 1 NA 1 0
#> 58 19.34 1 39 0 0
#> 188 16.16 1 46 0 1
#> 24 23.89 1 38 0 0
#> 90 20.94 1 50 0 1
#> 69 23.23 1 25 0 1
#> 139 21.49 1 63 1 0
#> 99 21.19 1 38 0 1
#> 79 16.23 1 54 1 0
#> 194 22.40 1 38 0 1
#> 89 11.44 1 NA 0 0
#> 108 18.29 1 39 0 1
#> 100 16.07 1 60 0 0
#> 99.1 21.19 1 38 0 1
#> 91 5.33 1 61 0 1
#> 61 10.12 1 36 0 1
#> 108.1 18.29 1 39 0 1
#> 139.1 21.49 1 63 1 0
#> 171 16.57 1 41 0 1
#> 170 19.54 1 43 0 1
#> 111 17.45 1 47 0 1
#> 187 9.92 1 39 1 0
#> 113 22.86 1 34 0 0
#> 61.1 10.12 1 36 0 1
#> 97 19.14 1 65 0 1
#> 97.1 19.14 1 65 0 1
#> 40 18.00 1 28 1 0
#> 99.2 21.19 1 38 0 1
#> 187.1 9.92 1 39 1 0
#> 43 12.10 1 61 0 1
#> 159 10.55 1 50 0 1
#> 177 12.53 1 75 0 0
#> 29 15.45 1 68 1 0
#> 159.1 10.55 1 50 0 1
#> 195 11.76 1 NA 1 0
#> 166 19.98 1 48 0 0
#> 129 23.41 1 53 1 0
#> 14 12.89 1 21 0 0
#> 157 15.10 1 47 0 0
#> 15 22.68 1 48 0 0
#> 30 17.43 1 78 0 0
#> 145 10.07 1 65 1 0
#> 60 13.15 1 38 1 0
#> 100.1 16.07 1 60 0 0
#> 195.1 11.76 1 NA 1 0
#> 183 9.24 1 67 1 0
#> 127 3.53 1 62 0 1
#> 50 10.02 1 NA 1 0
#> 106 16.67 1 49 1 0
#> 24.1 23.89 1 38 0 0
#> 155 13.08 1 26 0 0
#> 168 23.72 1 70 0 0
#> 195.2 11.76 1 NA 1 0
#> 90.1 20.94 1 50 0 1
#> 56 12.21 1 60 0 0
#> 76 19.22 1 54 0 1
#> 164 23.60 1 76 0 1
#> 6 15.64 1 39 0 0
#> 188.1 16.16 1 46 0 1
#> 158.1 20.14 1 74 1 0
#> 86 23.81 1 58 0 1
#> 18 15.21 1 49 1 0
#> 158.2 20.14 1 74 1 0
#> 36 21.19 1 48 0 1
#> 100.2 16.07 1 60 0 0
#> 96 14.54 1 33 0 1
#> 79.1 16.23 1 54 1 0
#> 57 14.46 1 45 0 1
#> 133 14.65 1 57 0 0
#> 158.3 20.14 1 74 1 0
#> 187.2 9.92 1 39 1 0
#> 90.2 20.94 1 50 0 1
#> 190 20.81 1 42 1 0
#> 55 19.34 1 69 0 1
#> 192 16.44 1 31 1 0
#> 36.1 21.19 1 48 0 1
#> 16 8.71 1 71 0 1
#> 184 17.77 1 38 0 0
#> 129.1 23.41 1 53 1 0
#> 60.1 13.15 1 38 1 0
#> 36.2 21.19 1 48 0 1
#> 70 7.38 1 30 1 0
#> 30.1 17.43 1 78 0 0
#> 14.1 12.89 1 21 0 0
#> 127.1 3.53 1 62 0 1
#> 26 15.77 1 49 0 1
#> 68 20.62 1 44 0 0
#> 139.2 21.49 1 63 1 0
#> 181.1 16.46 1 45 0 1
#> 77 7.27 1 67 0 1
#> 145.1 10.07 1 65 1 0
#> 5 16.43 1 51 0 1
#> 183.1 9.24 1 67 1 0
#> 43.1 12.10 1 61 0 1
#> 180 14.82 1 37 0 0
#> 16.1 8.71 1 71 0 1
#> 78 23.88 1 43 0 0
#> 13 14.34 1 54 0 1
#> 106.1 16.67 1 49 1 0
#> 181.2 16.46 1 45 0 1
#> 171.1 16.57 1 41 0 1
#> 190.1 20.81 1 42 1 0
#> 170.1 19.54 1 43 0 1
#> 92 22.92 1 47 0 1
#> 63 22.77 1 31 1 0
#> 77.1 7.27 1 67 0 1
#> 108.2 18.29 1 39 0 1
#> 13.1 14.34 1 54 0 1
#> 62 24.00 0 71 0 0
#> 137 24.00 0 45 1 0
#> 116 24.00 0 58 0 1
#> 48 24.00 0 31 1 0
#> 191 24.00 0 60 0 1
#> 64 24.00 0 43 0 0
#> 21 24.00 0 47 0 0
#> 116.1 24.00 0 58 0 1
#> 103 24.00 0 56 1 0
#> 83 24.00 0 6 0 0
#> 141 24.00 0 44 1 0
#> 47 24.00 0 38 0 1
#> 22 24.00 0 52 1 0
#> 83.1 24.00 0 6 0 0
#> 120 24.00 0 68 0 1
#> 152 24.00 0 36 0 1
#> 67 24.00 0 25 0 0
#> 71 24.00 0 51 0 0
#> 200 24.00 0 64 0 0
#> 72 24.00 0 40 0 1
#> 176 24.00 0 43 0 1
#> 94 24.00 0 51 0 1
#> 160 24.00 0 31 1 0
#> 146 24.00 0 63 1 0
#> 146.1 24.00 0 63 1 0
#> 112 24.00 0 61 0 0
#> 83.2 24.00 0 6 0 0
#> 20 24.00 0 46 1 0
#> 62.1 24.00 0 71 0 0
#> 2 24.00 0 9 0 0
#> 109 24.00 0 48 0 0
#> 74 24.00 0 43 0 1
#> 95 24.00 0 68 0 1
#> 103.1 24.00 0 56 1 0
#> 122 24.00 0 66 0 0
#> 109.1 24.00 0 48 0 0
#> 27 24.00 0 63 1 0
#> 191.1 24.00 0 60 0 1
#> 165 24.00 0 47 0 0
#> 65 24.00 0 57 1 0
#> 74.1 24.00 0 43 0 1
#> 73 24.00 0 NA 0 1
#> 115 24.00 0 NA 1 0
#> 165.1 24.00 0 47 0 0
#> 131 24.00 0 66 0 0
#> 104 24.00 0 50 1 0
#> 38 24.00 0 31 1 0
#> 141.1 24.00 0 44 1 0
#> 31 24.00 0 36 0 1
#> 115.1 24.00 0 NA 1 0
#> 31.1 24.00 0 36 0 1
#> 196 24.00 0 19 0 0
#> 104.1 24.00 0 50 1 0
#> 172 24.00 0 41 0 0
#> 152.1 24.00 0 36 0 1
#> 198 24.00 0 66 0 1
#> 109.2 24.00 0 48 0 0
#> 9 24.00 0 31 1 0
#> 73.1 24.00 0 NA 0 1
#> 84 24.00 0 39 0 1
#> 84.1 24.00 0 39 0 1
#> 62.2 24.00 0 71 0 0
#> 116.2 24.00 0 58 0 1
#> 65.1 24.00 0 57 1 0
#> 118 24.00 0 44 1 0
#> 147 24.00 0 76 1 0
#> 191.2 24.00 0 60 0 1
#> 71.1 24.00 0 51 0 0
#> 144 24.00 0 28 0 1
#> 151 24.00 0 42 0 0
#> 191.3 24.00 0 60 0 1
#> 9.1 24.00 0 31 1 0
#> 80 24.00 0 41 0 0
#> 143 24.00 0 51 0 0
#> 65.2 24.00 0 57 1 0
#> 82 24.00 0 34 0 0
#> 163 24.00 0 66 0 0
#> 132 24.00 0 55 0 0
#> 73.2 24.00 0 NA 0 1
#> 151.1 24.00 0 42 0 0
#> 1 24.00 0 23 1 0
#> 47.1 24.00 0 38 0 1
#> 2.1 24.00 0 9 0 0
#> 53 24.00 0 32 0 1
#> 103.2 24.00 0 56 1 0
#> 121 24.00 0 57 1 0
#> 115.2 24.00 0 NA 1 0
#> 54 24.00 0 53 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.917 NA NA NA
#> 2 age, Cure model 0.0144 NA NA NA
#> 3 grade_ii, Cure model 0.332 NA NA NA
#> 4 grade_iii, Cure model 0.934 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00325 NA NA NA
#> 2 grade_ii, Survival model 0.358 NA NA NA
#> 3 grade_iii, Survival model 0.392 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.91718 0.01437 0.33236 0.93422
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 256.4
#> Residual Deviance: 247 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.9171835 0.0143704 0.3323578 0.9342222
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.003246912 0.358462944 0.392066443
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.45405696 0.91452787 0.65375045 0.51636236 0.70516017 0.03385524
#> [7] 0.39501711 0.20775280 0.29792456 0.33452926 0.69072089 0.28382101
#> [13] 0.55899889 0.71939012 0.33452926 0.98214569 0.88905318 0.55899889
#> [19] 0.29792456 0.63851050 0.49874331 0.59926144 0.92086084 0.23926191
#> [25] 0.88905318 0.54231717 0.54231717 0.58310601 0.33452926 0.92086084
#> [31] 0.86305035 0.87612323 0.84975403 0.75459258 0.87612323 0.48962657
#> [37] 0.17523234 0.83647014 0.76853531 0.26922871 0.60725398 0.90185954
#> [43] 0.81648636 0.71939012 0.93949108 0.98814804 0.62301510 0.03385524
#> [49] 0.82979411 0.13313977 0.39501711 0.85640774 0.53368980 0.15545136
#> [55] 0.74754836 0.70516017 0.45405696 0.10984410 0.76158557 0.45405696
#> [61] 0.33452926 0.71939012 0.78932517 0.69072089 0.79620513 0.78240616
#> [67] 0.45405696 0.92086084 0.39501711 0.42476166 0.51636236 0.67592718
#> [73] 0.33452926 0.95182523 0.59119097 0.17523234 0.81648636 0.33452926
#> [79] 0.96402286 0.60725398 0.83647014 0.98814804 0.74049517 0.44424135
#> [85] 0.29792456 0.65375045 0.97011875 0.90185954 0.68335392 0.93949108
#> [91] 0.86305035 0.77547469 0.95182523 0.08194261 0.80304298 0.62301510
#> [97] 0.65375045 0.63851050 0.42476166 0.49874331 0.22390801 0.25450203
#> [103] 0.97011875 0.55899889 0.80304298 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000
#>
#> $Time
#> 158 101 181 58 188 24 90 69 139 99 79 194 108
#> 20.14 9.97 16.46 19.34 16.16 23.89 20.94 23.23 21.49 21.19 16.23 22.40 18.29
#> 100 99.1 91 61 108.1 139.1 171 170 111 187 113 61.1 97
#> 16.07 21.19 5.33 10.12 18.29 21.49 16.57 19.54 17.45 9.92 22.86 10.12 19.14
#> 97.1 40 99.2 187.1 43 159 177 29 159.1 166 129 14 157
#> 19.14 18.00 21.19 9.92 12.10 10.55 12.53 15.45 10.55 19.98 23.41 12.89 15.10
#> 15 30 145 60 100.1 183 127 106 24.1 155 168 90.1 56
#> 22.68 17.43 10.07 13.15 16.07 9.24 3.53 16.67 23.89 13.08 23.72 20.94 12.21
#> 76 164 6 188.1 158.1 86 18 158.2 36 100.2 96 79.1 57
#> 19.22 23.60 15.64 16.16 20.14 23.81 15.21 20.14 21.19 16.07 14.54 16.23 14.46
#> 133 158.3 187.2 90.2 190 55 192 36.1 16 184 129.1 60.1 36.2
#> 14.65 20.14 9.92 20.94 20.81 19.34 16.44 21.19 8.71 17.77 23.41 13.15 21.19
#> 70 30.1 14.1 127.1 26 68 139.2 181.1 77 145.1 5 183.1 43.1
#> 7.38 17.43 12.89 3.53 15.77 20.62 21.49 16.46 7.27 10.07 16.43 9.24 12.10
#> 180 16.1 78 13 106.1 181.2 171.1 190.1 170.1 92 63 77.1 108.2
#> 14.82 8.71 23.88 14.34 16.67 16.46 16.57 20.81 19.54 22.92 22.77 7.27 18.29
#> 13.1 62 137 116 48 191 64 21 116.1 103 83 141 47
#> 14.34 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 22 83.1 120 152 67 71 200 72 176 94 160 146 146.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 112 83.2 20 62.1 2 109 74 95 103.1 122 109.1 27 191.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165 65 74.1 165.1 131 104 38 141.1 31 31.1 196 104.1 172
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152.1 198 109.2 9 84 84.1 62.2 116.2 65.1 118 147 191.2 71.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 144 151 191.3 9.1 80 143 65.2 82 163 132 151.1 1 47.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 2.1 53 103.2 121 54
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[65]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.009375271 0.727144506 0.375336048
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.44495892 0.02160909 0.67466467
#> grade_iii, Cure model
#> 1.18488618
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 13 14.34 1 54 0 1
#> 139 21.49 1 63 1 0
#> 199 19.81 1 NA 0 1
#> 88 18.37 1 47 0 0
#> 10 10.53 1 34 0 0
#> 197 21.60 1 69 1 0
#> 183 9.24 1 67 1 0
#> 56 12.21 1 60 0 0
#> 88.1 18.37 1 47 0 0
#> 100 16.07 1 60 0 0
#> 59 10.16 1 NA 1 0
#> 154 12.63 1 20 1 0
#> 91 5.33 1 61 0 1
#> 170 19.54 1 43 0 1
#> 170.1 19.54 1 43 0 1
#> 26 15.77 1 49 0 1
#> 6 15.64 1 39 0 0
#> 124 9.73 1 NA 1 0
#> 89 11.44 1 NA 0 0
#> 58 19.34 1 39 0 0
#> 76 19.22 1 54 0 1
#> 187 9.92 1 39 1 0
#> 145 10.07 1 65 1 0
#> 92 22.92 1 47 0 1
#> 24 23.89 1 38 0 0
#> 39 15.59 1 37 0 1
#> 77 7.27 1 67 0 1
#> 43 12.10 1 61 0 1
#> 192 16.44 1 31 1 0
#> 10.1 10.53 1 34 0 0
#> 134 17.81 1 47 1 0
#> 24.1 23.89 1 38 0 0
#> 199.1 19.81 1 NA 0 1
#> 145.1 10.07 1 65 1 0
#> 195 11.76 1 NA 1 0
#> 188 16.16 1 46 0 1
#> 167 15.55 1 56 1 0
#> 15 22.68 1 48 0 0
#> 128 20.35 1 35 0 1
#> 106 16.67 1 49 1 0
#> 86 23.81 1 58 0 1
#> 16 8.71 1 71 0 1
#> 69 23.23 1 25 0 1
#> 63 22.77 1 31 1 0
#> 66 22.13 1 53 0 0
#> 70 7.38 1 30 1 0
#> 197.1 21.60 1 69 1 0
#> 166 19.98 1 48 0 0
#> 101 9.97 1 10 0 1
#> 150 20.33 1 48 0 0
#> 110 17.56 1 65 0 1
#> 77.1 7.27 1 67 0 1
#> 100.1 16.07 1 60 0 0
#> 181 16.46 1 45 0 1
#> 101.1 9.97 1 10 0 1
#> 187.1 9.92 1 39 1 0
#> 145.2 10.07 1 65 1 0
#> 171 16.57 1 41 0 1
#> 194 22.40 1 38 0 1
#> 106.1 16.67 1 49 1 0
#> 125 15.65 1 67 1 0
#> 68 20.62 1 44 0 0
#> 61 10.12 1 36 0 1
#> 58.1 19.34 1 39 0 0
#> 111 17.45 1 47 0 1
#> 16.1 8.71 1 71 0 1
#> 153 21.33 1 55 1 0
#> 25 6.32 1 34 1 0
#> 130 16.47 1 53 0 1
#> 68.1 20.62 1 44 0 0
#> 41 18.02 1 40 1 0
#> 127 3.53 1 62 0 1
#> 123 13.00 1 44 1 0
#> 194.1 22.40 1 38 0 1
#> 90 20.94 1 50 0 1
#> 76.1 19.22 1 54 0 1
#> 26.1 15.77 1 49 0 1
#> 149 8.37 1 33 1 0
#> 89.1 11.44 1 NA 0 0
#> 26.2 15.77 1 49 0 1
#> 105 19.75 1 60 0 0
#> 189 10.51 1 NA 1 0
#> 57 14.46 1 45 0 1
#> 110.1 17.56 1 65 0 1
#> 106.2 16.67 1 49 1 0
#> 66.1 22.13 1 53 0 0
#> 164 23.60 1 76 0 1
#> 158 20.14 1 74 1 0
#> 92.1 22.92 1 47 0 1
#> 166.1 19.98 1 48 0 0
#> 76.2 19.22 1 54 0 1
#> 97 19.14 1 65 0 1
#> 199.2 19.81 1 NA 0 1
#> 175 21.91 1 43 0 0
#> 167.1 15.55 1 56 1 0
#> 70.1 7.38 1 30 1 0
#> 125.1 15.65 1 67 1 0
#> 181.1 16.46 1 45 0 1
#> 167.2 15.55 1 56 1 0
#> 199.3 19.81 1 NA 0 1
#> 59.1 10.16 1 NA 1 0
#> 101.2 9.97 1 10 0 1
#> 41.1 18.02 1 40 1 0
#> 139.1 21.49 1 63 1 0
#> 91.1 5.33 1 61 0 1
#> 88.2 18.37 1 47 0 0
#> 164.1 23.60 1 76 0 1
#> 57.1 14.46 1 45 0 1
#> 180 14.82 1 37 0 0
#> 155 13.08 1 26 0 0
#> 159 10.55 1 50 0 1
#> 157 15.10 1 47 0 0
#> 38 24.00 0 31 1 0
#> 17 24.00 0 38 0 1
#> 53 24.00 0 32 0 1
#> 196 24.00 0 19 0 0
#> 46 24.00 0 71 0 0
#> 1 24.00 0 23 1 0
#> 115 24.00 0 NA 1 0
#> 71 24.00 0 51 0 0
#> 193 24.00 0 45 0 1
#> 191 24.00 0 60 0 1
#> 33 24.00 0 53 0 0
#> 71.1 24.00 0 51 0 0
#> 22 24.00 0 52 1 0
#> 112 24.00 0 61 0 0
#> 112.1 24.00 0 61 0 0
#> 186 24.00 0 45 1 0
#> 62 24.00 0 71 0 0
#> 160 24.00 0 31 1 0
#> 122 24.00 0 66 0 0
#> 109 24.00 0 48 0 0
#> 33.1 24.00 0 53 0 0
#> 44 24.00 0 56 0 0
#> 47 24.00 0 38 0 1
#> 46.1 24.00 0 71 0 0
#> 115.1 24.00 0 NA 1 0
#> 19 24.00 0 57 0 1
#> 152 24.00 0 36 0 1
#> 31 24.00 0 36 0 1
#> 1.1 24.00 0 23 1 0
#> 182 24.00 0 35 0 0
#> 9 24.00 0 31 1 0
#> 9.1 24.00 0 31 1 0
#> 165 24.00 0 47 0 0
#> 138 24.00 0 44 1 0
#> 87 24.00 0 27 0 0
#> 118 24.00 0 44 1 0
#> 27 24.00 0 63 1 0
#> 118.1 24.00 0 44 1 0
#> 53.1 24.00 0 32 0 1
#> 87.1 24.00 0 27 0 0
#> 191.1 24.00 0 60 0 1
#> 2 24.00 0 9 0 0
#> 162 24.00 0 51 0 0
#> 126 24.00 0 48 0 0
#> 35 24.00 0 51 0 0
#> 33.2 24.00 0 53 0 0
#> 173 24.00 0 19 0 1
#> 38.1 24.00 0 31 1 0
#> 109.1 24.00 0 48 0 0
#> 21 24.00 0 47 0 0
#> 74 24.00 0 43 0 1
#> 73 24.00 0 NA 0 1
#> 135 24.00 0 58 1 0
#> 94 24.00 0 51 0 1
#> 176 24.00 0 43 0 1
#> 20 24.00 0 46 1 0
#> 143 24.00 0 51 0 0
#> 165.1 24.00 0 47 0 0
#> 80 24.00 0 41 0 0
#> 122.1 24.00 0 66 0 0
#> 44.1 24.00 0 56 0 0
#> 163 24.00 0 66 0 0
#> 121 24.00 0 57 1 0
#> 185 24.00 0 44 1 0
#> 148 24.00 0 61 1 0
#> 12 24.00 0 63 0 0
#> 48 24.00 0 31 1 0
#> 198 24.00 0 66 0 1
#> 17.1 24.00 0 38 0 1
#> 87.2 24.00 0 27 0 0
#> 20.1 24.00 0 46 1 0
#> 3 24.00 0 31 1 0
#> 165.2 24.00 0 47 0 0
#> 20.2 24.00 0 46 1 0
#> 173.1 24.00 0 19 0 1
#> 193.1 24.00 0 45 0 1
#> 132 24.00 0 55 0 0
#> 67 24.00 0 25 0 0
#> 17.2 24.00 0 38 0 1
#> 38.2 24.00 0 31 1 0
#> 200 24.00 0 64 0 0
#> 196.1 24.00 0 19 0 0
#> 193.2 24.00 0 45 0 1
#> 162.1 24.00 0 51 0 0
#> 9.2 24.00 0 31 1 0
#> 74.1 24.00 0 43 0 1
#> 122.2 24.00 0 66 0 0
#> 9.3 24.00 0 31 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.44 NA NA NA
#> 2 age, Cure model 0.0216 NA NA NA
#> 3 grade_ii, Cure model 0.675 NA NA NA
#> 4 grade_iii, Cure model 1.18 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00938 NA NA NA
#> 2 grade_ii, Survival model 0.727 NA NA NA
#> 3 grade_iii, Survival model 0.375 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.44496 0.02161 0.67466 1.18489
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 256.5
#> Residual Deviance: 242.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.44495892 0.02160909 0.67466467 1.18488618
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.009375271 0.727144506 0.375336048
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.692032006 0.146892621 0.340858263 0.765150304 0.128526380 0.878574807
#> [7] 0.733840333 0.340858263 0.526813515 0.723488568 0.969735541 0.260101234
#> [13] 0.260101234 0.547461119 0.598933005 0.279911822 0.300161737 0.858239646
#> [19] 0.796595499 0.049289375 0.003570256 0.609406774 0.939495973 0.744255306
#> [25] 0.506319894 0.765150304 0.393087802 0.003570256 0.796595499 0.516561173
#> [31] 0.619875354 0.075007071 0.201854159 0.434907883 0.014888910 0.888789539
#> [37] 0.040062193 0.066440190 0.100814491 0.919432326 0.128526380 0.230598789
#> [43] 0.827604140 0.211335925 0.403523871 0.939495973 0.526813515 0.485819887
#> [49] 0.827604140 0.858239646 0.796595499 0.465164867 0.083944607 0.434907883
#> [55] 0.578278273 0.183295059 0.786070366 0.279911822 0.424348164 0.888789539
#> [61] 0.164932304 0.959655806 0.475479536 0.183295059 0.372312244 0.989864533
#> [67] 0.713029753 0.083944607 0.174092035 0.300161737 0.547461119 0.909219264
#> [73] 0.547461119 0.250021629 0.671265280 0.403523871 0.434907883 0.100814491
#> [79] 0.023241457 0.220974446 0.049289375 0.230598789 0.300161737 0.330389594
#> [85] 0.118872231 0.619875354 0.919432326 0.578278273 0.485819887 0.619875354
#> [91] 0.827604140 0.372312244 0.146892621 0.969735541 0.340858263 0.023241457
#> [97] 0.671265280 0.660815188 0.702513908 0.754696354 0.650413315 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 13 139 88 10 197 183 56 88.1 100 154 91 170 170.1
#> 14.34 21.49 18.37 10.53 21.60 9.24 12.21 18.37 16.07 12.63 5.33 19.54 19.54
#> 26 6 58 76 187 145 92 24 39 77 43 192 10.1
#> 15.77 15.64 19.34 19.22 9.92 10.07 22.92 23.89 15.59 7.27 12.10 16.44 10.53
#> 134 24.1 145.1 188 167 15 128 106 86 16 69 63 66
#> 17.81 23.89 10.07 16.16 15.55 22.68 20.35 16.67 23.81 8.71 23.23 22.77 22.13
#> 70 197.1 166 101 150 110 77.1 100.1 181 101.1 187.1 145.2 171
#> 7.38 21.60 19.98 9.97 20.33 17.56 7.27 16.07 16.46 9.97 9.92 10.07 16.57
#> 194 106.1 125 68 61 58.1 111 16.1 153 25 130 68.1 41
#> 22.40 16.67 15.65 20.62 10.12 19.34 17.45 8.71 21.33 6.32 16.47 20.62 18.02
#> 127 123 194.1 90 76.1 26.1 149 26.2 105 57 110.1 106.2 66.1
#> 3.53 13.00 22.40 20.94 19.22 15.77 8.37 15.77 19.75 14.46 17.56 16.67 22.13
#> 164 158 92.1 166.1 76.2 97 175 167.1 70.1 125.1 181.1 167.2 101.2
#> 23.60 20.14 22.92 19.98 19.22 19.14 21.91 15.55 7.38 15.65 16.46 15.55 9.97
#> 41.1 139.1 91.1 88.2 164.1 57.1 180 155 159 157 38 17 53
#> 18.02 21.49 5.33 18.37 23.60 14.46 14.82 13.08 10.55 15.10 24.00 24.00 24.00
#> 196 46 1 71 193 191 33 71.1 22 112 112.1 186 62
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 160 122 109 33.1 44 47 46.1 19 152 31 1.1 182 9
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9.1 165 138 87 118 27 118.1 53.1 87.1 191.1 2 162 126
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 35 33.2 173 38.1 109.1 21 74 135 94 176 20 143 165.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80 122.1 44.1 163 121 185 148 12 48 198 17.1 87.2 20.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3 165.2 20.2 173.1 193.1 132 67 17.2 38.2 200 196.1 193.2 162.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9.2 74.1 122.2 9.3
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[66]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01479616 0.24230431 0.09763259
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.60653704 0.01377497 -0.12596832
#> grade_iii, Cure model
#> 0.44060471
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 139 21.49 1 63 1 0
#> 177 12.53 1 75 0 0
#> 76 19.22 1 54 0 1
#> 129 23.41 1 53 1 0
#> 106 16.67 1 49 1 0
#> 108 18.29 1 39 0 1
#> 187 9.92 1 39 1 0
#> 149 8.37 1 33 1 0
#> 199 19.81 1 NA 0 1
#> 158 20.14 1 74 1 0
#> 114 13.68 1 NA 0 0
#> 42 12.43 1 49 0 1
#> 49 12.19 1 48 1 0
#> 60 13.15 1 38 1 0
#> 39 15.59 1 37 0 1
#> 43 12.10 1 61 0 1
#> 14 12.89 1 21 0 0
#> 175 21.91 1 43 0 0
#> 76.1 19.22 1 54 0 1
#> 100 16.07 1 60 0 0
#> 60.1 13.15 1 38 1 0
#> 105 19.75 1 60 0 0
#> 13 14.34 1 54 0 1
#> 197 21.60 1 69 1 0
#> 130 16.47 1 53 0 1
#> 91 5.33 1 61 0 1
#> 192 16.44 1 31 1 0
#> 52 10.42 1 52 0 1
#> 57 14.46 1 45 0 1
#> 58 19.34 1 39 0 0
#> 39.1 15.59 1 37 0 1
#> 195 11.76 1 NA 1 0
#> 167 15.55 1 56 1 0
#> 107 11.18 1 54 1 0
#> 96 14.54 1 33 0 1
#> 192.1 16.44 1 31 1 0
#> 111 17.45 1 47 0 1
#> 89 11.44 1 NA 0 0
#> 157 15.10 1 47 0 0
#> 25 6.32 1 34 1 0
#> 36 21.19 1 48 0 1
#> 30 17.43 1 78 0 0
#> 42.1 12.43 1 49 0 1
#> 91.1 5.33 1 61 0 1
#> 177.1 12.53 1 75 0 0
#> 86 23.81 1 58 0 1
#> 29 15.45 1 68 1 0
#> 92 22.92 1 47 0 1
#> 49.1 12.19 1 48 1 0
#> 105.1 19.75 1 60 0 0
#> 78 23.88 1 43 0 0
#> 63 22.77 1 31 1 0
#> 129.1 23.41 1 53 1 0
#> 149.1 8.37 1 33 1 0
#> 130.1 16.47 1 53 0 1
#> 164 23.60 1 76 0 1
#> 90 20.94 1 50 0 1
#> 68 20.62 1 44 0 0
#> 97 19.14 1 65 0 1
#> 39.2 15.59 1 37 0 1
#> 56 12.21 1 60 0 0
#> 88 18.37 1 47 0 0
#> 10 10.53 1 34 0 0
#> 52.1 10.42 1 52 0 1
#> 45 17.42 1 54 0 1
#> 51 18.23 1 83 0 1
#> 128 20.35 1 35 0 1
#> 199.1 19.81 1 NA 0 1
#> 14.1 12.89 1 21 0 0
#> 91.2 5.33 1 61 0 1
#> 110 17.56 1 65 0 1
#> 4 17.64 1 NA 0 1
#> 128.1 20.35 1 35 0 1
#> 52.2 10.42 1 52 0 1
#> 81 14.06 1 34 0 0
#> 133 14.65 1 57 0 0
#> 188 16.16 1 46 0 1
#> 58.1 19.34 1 39 0 0
#> 159 10.55 1 50 0 1
#> 41 18.02 1 40 1 0
#> 86.1 23.81 1 58 0 1
#> 184 17.77 1 38 0 0
#> 81.1 14.06 1 34 0 0
#> 89.1 11.44 1 NA 0 0
#> 41.1 18.02 1 40 1 0
#> 183 9.24 1 67 1 0
#> 153 21.33 1 55 1 0
#> 189 10.51 1 NA 1 0
#> 168 23.72 1 70 0 0
#> 89.2 11.44 1 NA 0 0
#> 140 12.68 1 59 1 0
#> 70 7.38 1 30 1 0
#> 88.1 18.37 1 47 0 0
#> 187.1 9.92 1 39 1 0
#> 168.1 23.72 1 70 0 0
#> 166 19.98 1 48 0 0
#> 49.2 12.19 1 48 1 0
#> 139.1 21.49 1 63 1 0
#> 117 17.46 1 26 0 1
#> 14.2 12.89 1 21 0 0
#> 77 7.27 1 67 0 1
#> 199.2 19.81 1 NA 0 1
#> 133.1 14.65 1 57 0 0
#> 125 15.65 1 67 1 0
#> 70.1 7.38 1 30 1 0
#> 6 15.64 1 39 0 0
#> 89.3 11.44 1 NA 0 0
#> 192.2 16.44 1 31 1 0
#> 170 19.54 1 43 0 1
#> 63.1 22.77 1 31 1 0
#> 92.1 22.92 1 47 0 1
#> 10.1 10.53 1 34 0 0
#> 126 24.00 0 48 0 0
#> 186 24.00 0 45 1 0
#> 1 24.00 0 23 1 0
#> 19 24.00 0 57 0 1
#> 75 24.00 0 21 1 0
#> 142 24.00 0 53 0 0
#> 33 24.00 0 53 0 0
#> 186.1 24.00 0 45 1 0
#> 126.1 24.00 0 48 0 0
#> 83 24.00 0 6 0 0
#> 165 24.00 0 47 0 0
#> 196 24.00 0 19 0 0
#> 98 24.00 0 34 1 0
#> 174 24.00 0 49 1 0
#> 138 24.00 0 44 1 0
#> 98.1 24.00 0 34 1 0
#> 126.2 24.00 0 48 0 0
#> 33.1 24.00 0 53 0 0
#> 46 24.00 0 71 0 0
#> 198 24.00 0 66 0 1
#> 143 24.00 0 51 0 0
#> 19.1 24.00 0 57 0 1
#> 102 24.00 0 49 0 0
#> 174.1 24.00 0 49 1 0
#> 156 24.00 0 50 1 0
#> 95 24.00 0 68 0 1
#> 71 24.00 0 51 0 0
#> 2 24.00 0 9 0 0
#> 38 24.00 0 31 1 0
#> 186.2 24.00 0 45 1 0
#> 94 24.00 0 51 0 1
#> 160 24.00 0 31 1 0
#> 20 24.00 0 46 1 0
#> 27 24.00 0 63 1 0
#> 98.2 24.00 0 34 1 0
#> 138.1 24.00 0 44 1 0
#> 46.1 24.00 0 71 0 0
#> 173 24.00 0 19 0 1
#> 83.1 24.00 0 6 0 0
#> 95.1 24.00 0 68 0 1
#> 198.1 24.00 0 66 0 1
#> 3 24.00 0 31 1 0
#> 121 24.00 0 57 1 0
#> 11 24.00 0 42 0 1
#> 193 24.00 0 45 0 1
#> 121.1 24.00 0 57 1 0
#> 95.2 24.00 0 68 0 1
#> 196.1 24.00 0 19 0 0
#> 131 24.00 0 66 0 0
#> 185 24.00 0 44 1 0
#> 9 24.00 0 31 1 0
#> 27.1 24.00 0 63 1 0
#> 138.2 24.00 0 44 1 0
#> 182 24.00 0 35 0 0
#> 9.1 24.00 0 31 1 0
#> 84 24.00 0 39 0 1
#> 104 24.00 0 50 1 0
#> 152 24.00 0 36 0 1
#> 75.1 24.00 0 21 1 0
#> 172 24.00 0 41 0 0
#> 47 24.00 0 38 0 1
#> 156.1 24.00 0 50 1 0
#> 132 24.00 0 55 0 0
#> 19.2 24.00 0 57 0 1
#> 7 24.00 0 37 1 0
#> 47.1 24.00 0 38 0 1
#> 161 24.00 0 45 0 0
#> 3.1 24.00 0 31 1 0
#> 95.3 24.00 0 68 0 1
#> 112 24.00 0 61 0 0
#> 198.2 24.00 0 66 0 1
#> 172.1 24.00 0 41 0 0
#> 3.2 24.00 0 31 1 0
#> 137 24.00 0 45 1 0
#> 122 24.00 0 66 0 0
#> 174.2 24.00 0 49 1 0
#> 54 24.00 0 53 1 0
#> 53 24.00 0 32 0 1
#> 152.1 24.00 0 36 0 1
#> 143.1 24.00 0 51 0 0
#> 193.1 24.00 0 45 0 1
#> 28 24.00 0 67 1 0
#> 126.3 24.00 0 48 0 0
#> 11.1 24.00 0 42 0 1
#> 102.1 24.00 0 49 0 0
#> 74 24.00 0 43 0 1
#> 135 24.00 0 58 1 0
#> 103 24.00 0 56 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.607 NA NA NA
#> 2 age, Cure model 0.0138 NA NA NA
#> 3 grade_ii, Cure model -0.126 NA NA NA
#> 4 grade_iii, Cure model 0.441 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0148 NA NA NA
#> 2 grade_ii, Survival model 0.242 NA NA NA
#> 3 grade_iii, Survival model 0.0976 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.60654 0.01377 -0.12597 0.44060
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 261.1
#> Residual Deviance: 255.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.60653704 0.01377497 -0.12596832 0.44060471
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01479616 0.24230431 0.09763259
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 2.739057e-02 5.603085e-01 1.031075e-01 5.814374e-03 2.241726e-01
#> [6] 1.385250e-01 7.993269e-01 8.482064e-01 6.206263e-02 5.881029e-01
#> [11] 6.311014e-01 4.812399e-01 3.256641e-01 6.749428e-01 5.073033e-01
#> [16] 2.071347e-02 1.031075e-01 2.933262e-01 4.812399e-01 7.280020e-02
#> [21] 4.428185e-01 2.392602e-02 2.337935e-01 9.483590e-01 2.534260e-01
#> [26] 7.518157e-01 4.302614e-01 9.048377e-02 3.256641e-01 3.586024e-01
#> [31] 6.900702e-01 4.178612e-01 2.534260e-01 1.964653e-01 3.817864e-01
#> [36] 9.313452e-01 3.885842e-02 2.054476e-01 5.881029e-01 9.483590e-01
#> [41] 5.603085e-01 3.982978e-04 3.700975e-01 9.989538e-03 6.311014e-01
#> [46] 7.280020e-02 6.021046e-05 1.515901e-02 5.814374e-03 8.482064e-01
#> [51] 2.337935e-01 3.917344e-03 4.316961e-02 4.769516e-02 1.165628e-01
#> [56] 3.256641e-01 6.165234e-01 1.237439e-01 7.207690e-01 7.518157e-01
#> [61] 2.147072e-01 1.462862e-01 5.243615e-02 5.073033e-01 9.483590e-01
#> [66] 1.789646e-01 5.243615e-02 7.518157e-01 4.555577e-01 3.936576e-01
#> [71] 2.829544e-01 9.048377e-02 7.053404e-01 1.543366e-01 3.982978e-04
#> [76] 1.705032e-01 4.555577e-01 1.543366e-01 8.316921e-01 3.475596e-02
#> [81] 1.561219e-03 5.466931e-01 8.811908e-01 1.237439e-01 7.993269e-01
#> [86] 1.561219e-03 6.732256e-02 6.311014e-01 2.739057e-02 1.876640e-01
#> [91] 5.073033e-01 9.144023e-01 3.936576e-01 3.039184e-01 8.811908e-01
#> [96] 3.147089e-01 2.534260e-01 8.432694e-02 1.515901e-02 9.989538e-03
#> [101] 7.207690e-01 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [106] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [186] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#>
#> $Time
#> 139 177 76 129 106 108 187 149 158 42 49 60 39
#> 21.49 12.53 19.22 23.41 16.67 18.29 9.92 8.37 20.14 12.43 12.19 13.15 15.59
#> 43 14 175 76.1 100 60.1 105 13 197 130 91 192 52
#> 12.10 12.89 21.91 19.22 16.07 13.15 19.75 14.34 21.60 16.47 5.33 16.44 10.42
#> 57 58 39.1 167 107 96 192.1 111 157 25 36 30 42.1
#> 14.46 19.34 15.59 15.55 11.18 14.54 16.44 17.45 15.10 6.32 21.19 17.43 12.43
#> 91.1 177.1 86 29 92 49.1 105.1 78 63 129.1 149.1 130.1 164
#> 5.33 12.53 23.81 15.45 22.92 12.19 19.75 23.88 22.77 23.41 8.37 16.47 23.60
#> 90 68 97 39.2 56 88 10 52.1 45 51 128 14.1 91.2
#> 20.94 20.62 19.14 15.59 12.21 18.37 10.53 10.42 17.42 18.23 20.35 12.89 5.33
#> 110 128.1 52.2 81 133 188 58.1 159 41 86.1 184 81.1 41.1
#> 17.56 20.35 10.42 14.06 14.65 16.16 19.34 10.55 18.02 23.81 17.77 14.06 18.02
#> 183 153 168 140 70 88.1 187.1 168.1 166 49.2 139.1 117 14.2
#> 9.24 21.33 23.72 12.68 7.38 18.37 9.92 23.72 19.98 12.19 21.49 17.46 12.89
#> 77 133.1 125 70.1 6 192.2 170 63.1 92.1 10.1 126 186 1
#> 7.27 14.65 15.65 7.38 15.64 16.44 19.54 22.77 22.92 10.53 24.00 24.00 24.00
#> 19 75 142 33 186.1 126.1 83 165 196 98 174 138 98.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126.2 33.1 46 198 143 19.1 102 174.1 156 95 71 2 38
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186.2 94 160 20 27 98.2 138.1 46.1 173 83.1 95.1 198.1 3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 121 11 193 121.1 95.2 196.1 131 185 9 27.1 138.2 182 9.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 84 104 152 75.1 172 47 156.1 132 19.2 7 47.1 161 3.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95.3 112 198.2 172.1 3.2 137 122 174.2 54 53 152.1 143.1 193.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28 126.3 11.1 102.1 74 135 103
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[67]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.02208804 0.66266039 0.52725767
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.88427053 0.01242424 0.29783252
#> grade_iii, Cure model
#> 1.23195431
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 41 18.02 1 40 1 0
#> 4 17.64 1 NA 0 1
#> 123 13.00 1 44 1 0
#> 68 20.62 1 44 0 0
#> 42 12.43 1 49 0 1
#> 189 10.51 1 NA 1 0
#> 183 9.24 1 67 1 0
#> 4.1 17.64 1 NA 0 1
#> 117 17.46 1 26 0 1
#> 153 21.33 1 55 1 0
#> 59 10.16 1 NA 1 0
#> 195 11.76 1 NA 1 0
#> 40 18.00 1 28 1 0
#> 91 5.33 1 61 0 1
#> 181 16.46 1 45 0 1
#> 189.1 10.51 1 NA 1 0
#> 85 16.44 1 36 0 0
#> 183.1 9.24 1 67 1 0
#> 77 7.27 1 67 0 1
#> 190 20.81 1 42 1 0
#> 90 20.94 1 50 0 1
#> 107 11.18 1 54 1 0
#> 99 21.19 1 38 0 1
#> 179 18.63 1 42 0 0
#> 49 12.19 1 48 1 0
#> 154 12.63 1 20 1 0
#> 125 15.65 1 67 1 0
#> 154.1 12.63 1 20 1 0
#> 39 15.59 1 37 0 1
#> 59.1 10.16 1 NA 1 0
#> 90.1 20.94 1 50 0 1
#> 91.1 5.33 1 61 0 1
#> 93 10.33 1 52 0 1
#> 16 8.71 1 71 0 1
#> 189.2 10.51 1 NA 1 0
#> 171 16.57 1 41 0 1
#> 140 12.68 1 59 1 0
#> 42.1 12.43 1 49 0 1
#> 154.2 12.63 1 20 1 0
#> 91.2 5.33 1 61 0 1
#> 56 12.21 1 60 0 0
#> 140.1 12.68 1 59 1 0
#> 70 7.38 1 30 1 0
#> 187 9.92 1 39 1 0
#> 133 14.65 1 57 0 0
#> 150 20.33 1 48 0 0
#> 192 16.44 1 31 1 0
#> 166 19.98 1 48 0 0
#> 171.1 16.57 1 41 0 1
#> 111 17.45 1 47 0 1
#> 107.1 11.18 1 54 1 0
#> 43 12.10 1 61 0 1
#> 195.1 11.76 1 NA 1 0
#> 45 17.42 1 54 0 1
#> 184 17.77 1 38 0 0
#> 183.2 9.24 1 67 1 0
#> 140.2 12.68 1 59 1 0
#> 52 10.42 1 52 0 1
#> 111.1 17.45 1 47 0 1
#> 123.1 13.00 1 44 1 0
#> 13 14.34 1 54 0 1
#> 125.1 15.65 1 67 1 0
#> 187.1 9.92 1 39 1 0
#> 15 22.68 1 48 0 0
#> 108 18.29 1 39 0 1
#> 155 13.08 1 26 0 0
#> 130 16.47 1 53 0 1
#> 92 22.92 1 47 0 1
#> 58 19.34 1 39 0 0
#> 78 23.88 1 43 0 0
#> 195.2 11.76 1 NA 1 0
#> 175 21.91 1 43 0 0
#> 29 15.45 1 68 1 0
#> 16.1 8.71 1 71 0 1
#> 60 13.15 1 38 1 0
#> 49.1 12.19 1 48 1 0
#> 105 19.75 1 60 0 0
#> 157 15.10 1 47 0 0
#> 96 14.54 1 33 0 1
#> 166.1 19.98 1 48 0 0
#> 199 19.81 1 NA 0 1
#> 195.3 11.76 1 NA 1 0
#> 107.2 11.18 1 54 1 0
#> 42.2 12.43 1 49 0 1
#> 25 6.32 1 34 1 0
#> 107.3 11.18 1 54 1 0
#> 60.1 13.15 1 38 1 0
#> 13.1 14.34 1 54 0 1
#> 125.2 15.65 1 67 1 0
#> 133.1 14.65 1 57 0 0
#> 194 22.40 1 38 0 1
#> 136 21.83 1 43 0 1
#> 26 15.77 1 49 0 1
#> 139 21.49 1 63 1 0
#> 153.1 21.33 1 55 1 0
#> 57 14.46 1 45 0 1
#> 56.1 12.21 1 60 0 0
#> 184.1 17.77 1 38 0 0
#> 30 17.43 1 78 0 0
#> 60.2 13.15 1 38 1 0
#> 43.1 12.10 1 61 0 1
#> 199.1 19.81 1 NA 0 1
#> 77.1 7.27 1 67 0 1
#> 23 16.92 1 61 0 0
#> 63 22.77 1 31 1 0
#> 81 14.06 1 34 0 0
#> 5 16.43 1 51 0 1
#> 195.4 11.76 1 NA 1 0
#> 43.2 12.10 1 61 0 1
#> 155.1 13.08 1 26 0 0
#> 5.1 16.43 1 51 0 1
#> 117.1 17.46 1 26 0 1
#> 176 24.00 0 43 0 1
#> 28 24.00 0 67 1 0
#> 163 24.00 0 66 0 0
#> 98 24.00 0 34 1 0
#> 34 24.00 0 36 0 0
#> 48 24.00 0 31 1 0
#> 54 24.00 0 53 1 0
#> 95 24.00 0 68 0 1
#> 182 24.00 0 35 0 0
#> 2 24.00 0 9 0 0
#> 27 24.00 0 63 1 0
#> 21 24.00 0 47 0 0
#> 115 24.00 0 NA 1 0
#> 178 24.00 0 52 1 0
#> 65 24.00 0 57 1 0
#> 152 24.00 0 36 0 1
#> 9 24.00 0 31 1 0
#> 27.1 24.00 0 63 1 0
#> 72 24.00 0 40 0 1
#> 141 24.00 0 44 1 0
#> 126 24.00 0 48 0 0
#> 119 24.00 0 17 0 0
#> 33 24.00 0 53 0 0
#> 162 24.00 0 51 0 0
#> 112 24.00 0 61 0 0
#> 115.1 24.00 0 NA 1 0
#> 3 24.00 0 31 1 0
#> 53 24.00 0 32 0 1
#> 1 24.00 0 23 1 0
#> 21.1 24.00 0 47 0 0
#> 109 24.00 0 48 0 0
#> 200 24.00 0 64 0 0
#> 95.1 24.00 0 68 0 1
#> 138 24.00 0 44 1 0
#> 115.2 24.00 0 NA 1 0
#> 28.1 24.00 0 67 1 0
#> 22 24.00 0 52 1 0
#> 146 24.00 0 63 1 0
#> 67 24.00 0 25 0 0
#> 122 24.00 0 66 0 0
#> 34.1 24.00 0 36 0 0
#> 83 24.00 0 6 0 0
#> 115.3 24.00 0 NA 1 0
#> 1.1 24.00 0 23 1 0
#> 151 24.00 0 42 0 0
#> 162.1 24.00 0 51 0 0
#> 20 24.00 0 46 1 0
#> 135 24.00 0 58 1 0
#> 71 24.00 0 51 0 0
#> 102 24.00 0 49 0 0
#> 47 24.00 0 38 0 1
#> 3.1 24.00 0 31 1 0
#> 137 24.00 0 45 1 0
#> 165 24.00 0 47 0 0
#> 28.2 24.00 0 67 1 0
#> 20.1 24.00 0 46 1 0
#> 119.1 24.00 0 17 0 0
#> 141.1 24.00 0 44 1 0
#> 191 24.00 0 60 0 1
#> 82 24.00 0 34 0 0
#> 3.2 24.00 0 31 1 0
#> 31 24.00 0 36 0 1
#> 65.1 24.00 0 57 1 0
#> 178.1 24.00 0 52 1 0
#> 198 24.00 0 66 0 1
#> 120 24.00 0 68 0 1
#> 142 24.00 0 53 0 0
#> 132 24.00 0 55 0 0
#> 22.1 24.00 0 52 1 0
#> 20.2 24.00 0 46 1 0
#> 44 24.00 0 56 0 0
#> 173 24.00 0 19 0 1
#> 67.1 24.00 0 25 0 0
#> 176.1 24.00 0 43 0 1
#> 17 24.00 0 38 0 1
#> 196 24.00 0 19 0 0
#> 131 24.00 0 66 0 0
#> 87 24.00 0 27 0 0
#> 73 24.00 0 NA 0 1
#> 186 24.00 0 45 1 0
#> 143 24.00 0 51 0 0
#> 156 24.00 0 50 1 0
#> 19 24.00 0 57 0 1
#> 54.1 24.00 0 53 1 0
#> 174 24.00 0 49 1 0
#> 160 24.00 0 31 1 0
#> 185 24.00 0 44 1 0
#> 186.1 24.00 0 45 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.884 NA NA NA
#> 2 age, Cure model 0.0124 NA NA NA
#> 3 grade_ii, Cure model 0.298 NA NA NA
#> 4 grade_iii, Cure model 1.23 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0221 NA NA NA
#> 2 grade_ii, Survival model 0.663 NA NA NA
#> 3 grade_iii, Survival model 0.527 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.88427 0.01242 0.29783 1.23195
#>
#> Degrees of Freedom: 180 Total (i.e. Null); 177 Residual
#> Null Deviance: 249.7
#> Residual Deviance: 237.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.88427053 0.01242424 0.29783252 1.23195431
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.02208804 0.66266039 0.52725767
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.7098556 0.8999391 0.6404366 0.9252914 0.9737329 0.7392827 0.5723381
#> [8] 0.7174815 0.9937997 0.8009196 0.8062464 0.9737329 0.9873402 0.6306470
#> [15] 0.6099763 0.9537156 0.5978471 0.6936937 0.9399805 0.9160688 0.8312128
#> [22] 0.9160688 0.8439071 0.6099763 0.9937997 0.9663675 0.9806506 0.7842448
#> [29] 0.9066549 0.9252914 0.9160688 0.9937997 0.9341604 0.9066549 0.9851179
#> [36] 0.9688547 0.8561431 0.6499865 0.8062464 0.6592787 0.7842448 0.7531224
#> [43] 0.9537156 0.9456394 0.7723157 0.7249022 0.9737329 0.9066549 0.9638521
#> [50] 0.7531224 0.8999391 0.8716243 0.8312128 0.9688547 0.4477912 0.7019146
#> [57] 0.8930100 0.7954629 0.3576258 0.6853212 0.2429033 0.5081128 0.8480999
#> [64] 0.9806506 0.8825737 0.9399805 0.6768064 0.8521388 0.8639492 0.6592787
#> [71] 0.9537156 0.9252914 0.9916547 0.9537156 0.8825737 0.8716243 0.8312128
#> [78] 0.8561431 0.4806928 0.5333728 0.8264046 0.5551479 0.5723381 0.8678171
#> [85] 0.9341604 0.7249022 0.7660622 0.8825737 0.9456394 0.9873402 0.7783453
#> [92] 0.4095985 0.8789301 0.8165882 0.9456394 0.8930100 0.8165882 0.7392827
#> [99] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [106] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#>
#> $Time
#> 41 123 68 42 183 117 153 40 91 181 85 183.1 77
#> 18.02 13.00 20.62 12.43 9.24 17.46 21.33 18.00 5.33 16.46 16.44 9.24 7.27
#> 190 90 107 99 179 49 154 125 154.1 39 90.1 91.1 93
#> 20.81 20.94 11.18 21.19 18.63 12.19 12.63 15.65 12.63 15.59 20.94 5.33 10.33
#> 16 171 140 42.1 154.2 91.2 56 140.1 70 187 133 150 192
#> 8.71 16.57 12.68 12.43 12.63 5.33 12.21 12.68 7.38 9.92 14.65 20.33 16.44
#> 166 171.1 111 107.1 43 45 184 183.2 140.2 52 111.1 123.1 13
#> 19.98 16.57 17.45 11.18 12.10 17.42 17.77 9.24 12.68 10.42 17.45 13.00 14.34
#> 125.1 187.1 15 108 155 130 92 58 78 175 29 16.1 60
#> 15.65 9.92 22.68 18.29 13.08 16.47 22.92 19.34 23.88 21.91 15.45 8.71 13.15
#> 49.1 105 157 96 166.1 107.2 42.2 25 107.3 60.1 13.1 125.2 133.1
#> 12.19 19.75 15.10 14.54 19.98 11.18 12.43 6.32 11.18 13.15 14.34 15.65 14.65
#> 194 136 26 139 153.1 57 56.1 184.1 30 60.2 43.1 77.1 23
#> 22.40 21.83 15.77 21.49 21.33 14.46 12.21 17.77 17.43 13.15 12.10 7.27 16.92
#> 63 81 5 43.2 155.1 5.1 117.1 176 28 163 98 34 48
#> 22.77 14.06 16.43 12.10 13.08 16.43 17.46 24.00 24.00 24.00 24.00 24.00 24.00
#> 54 95 182 2 27 21 178 65 152 9 27.1 72 141
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126 119 33 162 112 3 53 1 21.1 109 200 95.1 138
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28.1 22 146 67 122 34.1 83 1.1 151 162.1 20 135 71
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 102 47 3.1 137 165 28.2 20.1 119.1 141.1 191 82 3.2 31
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 65.1 178.1 198 120 142 132 22.1 20.2 44 173 67.1 176.1 17
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 196 131 87 186 143 156 19 54.1 174 160 185 186.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[68]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.001104396 0.561182227 0.565221754
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.254881360 0.005057954 -0.083197648
#> grade_iii, Cure model
#> 0.520031854
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 24 23.89 1 38 0 0
#> 26 15.77 1 49 0 1
#> 60 13.15 1 38 1 0
#> 68 20.62 1 44 0 0
#> 130 16.47 1 53 0 1
#> 36 21.19 1 48 0 1
#> 79 16.23 1 54 1 0
#> 134 17.81 1 47 1 0
#> 37 12.52 1 57 1 0
#> 51 18.23 1 83 0 1
#> 188 16.16 1 46 0 1
#> 24.1 23.89 1 38 0 0
#> 59 10.16 1 NA 1 0
#> 111 17.45 1 47 0 1
#> 51.1 18.23 1 83 0 1
#> 171 16.57 1 41 0 1
#> 49 12.19 1 48 1 0
#> 23 16.92 1 61 0 0
#> 184 17.77 1 38 0 0
#> 159 10.55 1 50 0 1
#> 106 16.67 1 49 1 0
#> 56 12.21 1 60 0 0
#> 195 11.76 1 NA 1 0
#> 168 23.72 1 70 0 0
#> 85 16.44 1 36 0 0
#> 192 16.44 1 31 1 0
#> 41 18.02 1 40 1 0
#> 111.1 17.45 1 47 0 1
#> 105 19.75 1 60 0 0
#> 194 22.40 1 38 0 1
#> 139 21.49 1 63 1 0
#> 100 16.07 1 60 0 0
#> 192.1 16.44 1 31 1 0
#> 166 19.98 1 48 0 0
#> 56.1 12.21 1 60 0 0
#> 36.1 21.19 1 48 0 1
#> 59.1 10.16 1 NA 1 0
#> 40 18.00 1 28 1 0
#> 52 10.42 1 52 0 1
#> 125 15.65 1 67 1 0
#> 32 20.90 1 37 1 0
#> 96 14.54 1 33 0 1
#> 101 9.97 1 10 0 1
#> 57 14.46 1 45 0 1
#> 159.1 10.55 1 50 0 1
#> 113 22.86 1 34 0 0
#> 50 10.02 1 NA 1 0
#> 60.1 13.15 1 38 1 0
#> 58 19.34 1 39 0 0
#> 96.1 14.54 1 33 0 1
#> 25 6.32 1 34 1 0
#> 88 18.37 1 47 0 0
#> 70 7.38 1 30 1 0
#> 16 8.71 1 71 0 1
#> 78 23.88 1 43 0 0
#> 179 18.63 1 42 0 0
#> 199 19.81 1 NA 0 1
#> 93 10.33 1 52 0 1
#> 127 3.53 1 62 0 1
#> 25.1 6.32 1 34 1 0
#> 124 9.73 1 NA 1 0
#> 110 17.56 1 65 0 1
#> 56.2 12.21 1 60 0 0
#> 24.2 23.89 1 38 0 0
#> 4 17.64 1 NA 0 1
#> 158 20.14 1 74 1 0
#> 68.1 20.62 1 44 0 0
#> 171.1 16.57 1 41 0 1
#> 39 15.59 1 37 0 1
#> 154 12.63 1 20 1 0
#> 166.1 19.98 1 48 0 0
#> 14 12.89 1 21 0 0
#> 130.1 16.47 1 53 0 1
#> 14.1 12.89 1 21 0 0
#> 50.1 10.02 1 NA 1 0
#> 145 10.07 1 65 1 0
#> 10 10.53 1 34 0 0
#> 50.2 10.02 1 NA 1 0
#> 199.1 19.81 1 NA 0 1
#> 63 22.77 1 31 1 0
#> 158.1 20.14 1 74 1 0
#> 25.2 6.32 1 34 1 0
#> 114 13.68 1 NA 0 0
#> 50.3 10.02 1 NA 1 0
#> 180 14.82 1 37 0 0
#> 86 23.81 1 58 0 1
#> 194.1 22.40 1 38 0 1
#> 194.2 22.40 1 38 0 1
#> 114.1 13.68 1 NA 0 0
#> 63.1 22.77 1 31 1 0
#> 6 15.64 1 39 0 0
#> 52.1 10.42 1 52 0 1
#> 85.1 16.44 1 36 0 0
#> 24.3 23.89 1 38 0 0
#> 93.1 10.33 1 52 0 1
#> 81 14.06 1 34 0 0
#> 127.1 3.53 1 62 0 1
#> 50.4 10.02 1 NA 1 0
#> 56.3 12.21 1 60 0 0
#> 114.2 13.68 1 NA 0 0
#> 125.1 15.65 1 67 1 0
#> 188.1 16.16 1 46 0 1
#> 159.2 10.55 1 50 0 1
#> 194.3 22.40 1 38 0 1
#> 117 17.46 1 26 0 1
#> 43 12.10 1 61 0 1
#> 189 10.51 1 NA 1 0
#> 14.2 12.89 1 21 0 0
#> 164 23.60 1 76 0 1
#> 106.1 16.67 1 49 1 0
#> 63.2 22.77 1 31 1 0
#> 97 19.14 1 65 0 1
#> 143 24.00 0 51 0 0
#> 146 24.00 0 63 1 0
#> 17 24.00 0 38 0 1
#> 142 24.00 0 53 0 0
#> 2 24.00 0 9 0 0
#> 7 24.00 0 37 1 0
#> 33 24.00 0 53 0 0
#> 83 24.00 0 6 0 0
#> 17.1 24.00 0 38 0 1
#> 115 24.00 0 NA 1 0
#> 198 24.00 0 66 0 1
#> 198.1 24.00 0 66 0 1
#> 1 24.00 0 23 1 0
#> 19 24.00 0 57 0 1
#> 160 24.00 0 31 1 0
#> 20 24.00 0 46 1 0
#> 2.1 24.00 0 9 0 0
#> 22 24.00 0 52 1 0
#> 102 24.00 0 49 0 0
#> 138 24.00 0 44 1 0
#> 75 24.00 0 21 1 0
#> 44 24.00 0 56 0 0
#> 33.1 24.00 0 53 0 0
#> 31 24.00 0 36 0 1
#> 46 24.00 0 71 0 0
#> 19.1 24.00 0 57 0 1
#> 122 24.00 0 66 0 0
#> 109 24.00 0 48 0 0
#> 173 24.00 0 19 0 1
#> 27 24.00 0 63 1 0
#> 118 24.00 0 44 1 0
#> 53 24.00 0 32 0 1
#> 147 24.00 0 76 1 0
#> 20.1 24.00 0 46 1 0
#> 174 24.00 0 49 1 0
#> 126 24.00 0 48 0 0
#> 143.1 24.00 0 51 0 0
#> 173.1 24.00 0 19 0 1
#> 72 24.00 0 40 0 1
#> 151 24.00 0 42 0 0
#> 137 24.00 0 45 1 0
#> 103 24.00 0 56 1 0
#> 135 24.00 0 58 1 0
#> 7.1 24.00 0 37 1 0
#> 83.1 24.00 0 6 0 0
#> 65 24.00 0 57 1 0
#> 27.1 24.00 0 63 1 0
#> 131 24.00 0 66 0 0
#> 2.2 24.00 0 9 0 0
#> 74 24.00 0 43 0 1
#> 121 24.00 0 57 1 0
#> 11 24.00 0 42 0 1
#> 163 24.00 0 66 0 0
#> 126.1 24.00 0 48 0 0
#> 109.1 24.00 0 48 0 0
#> 53.1 24.00 0 32 0 1
#> 115.1 24.00 0 NA 1 0
#> 33.2 24.00 0 53 0 0
#> 126.2 24.00 0 48 0 0
#> 160.1 24.00 0 31 1 0
#> 122.1 24.00 0 66 0 0
#> 146.1 24.00 0 63 1 0
#> 144 24.00 0 28 0 1
#> 83.2 24.00 0 6 0 0
#> 9 24.00 0 31 1 0
#> 163.1 24.00 0 66 0 0
#> 11.1 24.00 0 42 0 1
#> 200 24.00 0 64 0 0
#> 20.2 24.00 0 46 1 0
#> 75.1 24.00 0 21 1 0
#> 95 24.00 0 68 0 1
#> 193 24.00 0 45 0 1
#> 116 24.00 0 58 0 1
#> 27.2 24.00 0 63 1 0
#> 182 24.00 0 35 0 0
#> 9.1 24.00 0 31 1 0
#> 173.2 24.00 0 19 0 1
#> 54 24.00 0 53 1 0
#> 2.3 24.00 0 9 0 0
#> 11.2 24.00 0 42 0 1
#> 27.3 24.00 0 63 1 0
#> 72.1 24.00 0 40 0 1
#> 72.2 24.00 0 40 0 1
#> 112 24.00 0 61 0 0
#> 174.1 24.00 0 49 1 0
#> 115.2 24.00 0 NA 1 0
#> 151.1 24.00 0 42 0 0
#> 62 24.00 0 71 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.255 NA NA NA
#> 2 age, Cure model 0.00506 NA NA NA
#> 3 grade_ii, Cure model -0.0832 NA NA NA
#> 4 grade_iii, Cure model 0.520 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00110 NA NA NA
#> 2 grade_ii, Survival model 0.561 NA NA NA
#> 3 grade_iii, Survival model 0.565 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.254881 0.005058 -0.083198 0.520032
#>
#> Degrees of Freedom: 180 Total (i.e. Null); 177 Residual
#> Null Deviance: 250.3
#> Residual Deviance: 246.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.254881360 0.005057954 -0.083197648 0.520031854
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.001104396 0.561182227 0.565221754
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.03347557 0.68637343 0.76963287 0.33073588 0.59912366 0.29630424
#> [7] 0.65180720 0.49314721 0.81766156 0.45149908 0.66059132 0.03347557
#> [13] 0.53332790 0.45149908 0.58080929 0.85708975 0.55244093 0.50328278
#> [19] 0.87289995 0.56209254 0.82562338 0.13669615 0.61707602 0.61707602
#> [25] 0.47244035 0.53332790 0.39671319 0.23627693 0.28391516 0.67773808
#> [31] 0.61707602 0.37496071 0.82562338 0.29630424 0.48287140 0.90366435
#> [37] 0.69493691 0.31930616 0.73687739 0.94152678 0.75326880 0.87289995
#> [43] 0.17500991 0.76963287 0.40776248 0.73687739 0.96387901 0.44059426
#> [49] 0.95646734 0.94901550 0.09498092 0.42970308 0.91891181 0.98560134
#> [55] 0.96387901 0.51342675 0.82562338 0.03347557 0.35327351 0.33073588
#> [61] 0.58080929 0.72013665 0.80964937 0.37496071 0.78568209 0.59912366
#> [67] 0.78568209 0.93399370 0.89592139 0.19351938 0.35327351 0.96387901
#> [73] 0.72850510 0.11703558 0.23627693 0.23627693 0.19351938 0.71170063
#> [79] 0.90366435 0.61707602 0.03347557 0.91891181 0.76144921 0.98560134
#> [85] 0.82562338 0.69493691 0.66059132 0.87289995 0.23627693 0.52344447
#> [91] 0.86501815 0.78568209 0.15657406 0.56209254 0.19351938 0.41882441
#> [97] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000
#>
#> $Time
#> 24 26 60 68 130 36 79 134 37 51 188 24.1 111
#> 23.89 15.77 13.15 20.62 16.47 21.19 16.23 17.81 12.52 18.23 16.16 23.89 17.45
#> 51.1 171 49 23 184 159 106 56 168 85 192 41 111.1
#> 18.23 16.57 12.19 16.92 17.77 10.55 16.67 12.21 23.72 16.44 16.44 18.02 17.45
#> 105 194 139 100 192.1 166 56.1 36.1 40 52 125 32 96
#> 19.75 22.40 21.49 16.07 16.44 19.98 12.21 21.19 18.00 10.42 15.65 20.90 14.54
#> 101 57 159.1 113 60.1 58 96.1 25 88 70 16 78 179
#> 9.97 14.46 10.55 22.86 13.15 19.34 14.54 6.32 18.37 7.38 8.71 23.88 18.63
#> 93 127 25.1 110 56.2 24.2 158 68.1 171.1 39 154 166.1 14
#> 10.33 3.53 6.32 17.56 12.21 23.89 20.14 20.62 16.57 15.59 12.63 19.98 12.89
#> 130.1 14.1 145 10 63 158.1 25.2 180 86 194.1 194.2 63.1 6
#> 16.47 12.89 10.07 10.53 22.77 20.14 6.32 14.82 23.81 22.40 22.40 22.77 15.64
#> 52.1 85.1 24.3 93.1 81 127.1 56.3 125.1 188.1 159.2 194.3 117 43
#> 10.42 16.44 23.89 10.33 14.06 3.53 12.21 15.65 16.16 10.55 22.40 17.46 12.10
#> 14.2 164 106.1 63.2 97 143 146 17 142 2 7 33 83
#> 12.89 23.60 16.67 22.77 19.14 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 17.1 198 198.1 1 19 160 20 2.1 22 102 138 75 44
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33.1 31 46 19.1 122 109 173 27 118 53 147 20.1 174
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126 143.1 173.1 72 151 137 103 135 7.1 83.1 65 27.1 131
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 2.2 74 121 11 163 126.1 109.1 53.1 33.2 126.2 160.1 122.1 146.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 144 83.2 9 163.1 11.1 200 20.2 75.1 95 193 116 27.2 182
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9.1 173.2 54 2.3 11.2 27.3 72.1 72.2 112 174.1 151.1 62
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[69]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.02203607 0.91404871 0.60067231
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.027312012 0.002938357 -0.247765118
#> grade_iii, Cure model
#> 0.288922374
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 86 23.81 1 58 0 1
#> 108 18.29 1 39 0 1
#> 180 14.82 1 37 0 0
#> 105 19.75 1 60 0 0
#> 127 3.53 1 62 0 1
#> 39 15.59 1 37 0 1
#> 128 20.35 1 35 0 1
#> 133 14.65 1 57 0 0
#> 78 23.88 1 43 0 0
#> 183 9.24 1 67 1 0
#> 30 17.43 1 78 0 0
#> 171 16.57 1 41 0 1
#> 166 19.98 1 48 0 0
#> 195 11.76 1 NA 1 0
#> 139 21.49 1 63 1 0
#> 36 21.19 1 48 0 1
#> 37 12.52 1 57 1 0
#> 10 10.53 1 34 0 0
#> 56 12.21 1 60 0 0
#> 110 17.56 1 65 0 1
#> 169 22.41 1 46 0 0
#> 177 12.53 1 75 0 0
#> 145 10.07 1 65 1 0
#> 157 15.10 1 47 0 0
#> 49 12.19 1 48 1 0
#> 68 20.62 1 44 0 0
#> 76 19.22 1 54 0 1
#> 79 16.23 1 54 1 0
#> 187 9.92 1 39 1 0
#> 16 8.71 1 71 0 1
#> 184 17.77 1 38 0 0
#> 168 23.72 1 70 0 0
#> 101 9.97 1 10 0 1
#> 171.1 16.57 1 41 0 1
#> 180.1 14.82 1 37 0 0
#> 85 16.44 1 36 0 0
#> 76.1 19.22 1 54 0 1
#> 155 13.08 1 26 0 0
#> 155.1 13.08 1 26 0 0
#> 127.1 3.53 1 62 0 1
#> 123 13.00 1 44 1 0
#> 100 16.07 1 60 0 0
#> 130 16.47 1 53 0 1
#> 195.1 11.76 1 NA 1 0
#> 169.1 22.41 1 46 0 0
#> 79.1 16.23 1 54 1 0
#> 97 19.14 1 65 0 1
#> 139.1 21.49 1 63 1 0
#> 26 15.77 1 49 0 1
#> 154 12.63 1 20 1 0
#> 25 6.32 1 34 1 0
#> 13 14.34 1 54 0 1
#> 168.1 23.72 1 70 0 0
#> 111 17.45 1 47 0 1
#> 159 10.55 1 50 0 1
#> 96 14.54 1 33 0 1
#> 177.1 12.53 1 75 0 0
#> 43 12.10 1 61 0 1
#> 42 12.43 1 49 0 1
#> 10.1 10.53 1 34 0 0
#> 42.1 12.43 1 49 0 1
#> 183.1 9.24 1 67 1 0
#> 197 21.60 1 69 1 0
#> 6 15.64 1 39 0 0
#> 76.2 19.22 1 54 0 1
#> 45 17.42 1 54 0 1
#> 133.1 14.65 1 57 0 0
#> 139.2 21.49 1 63 1 0
#> 13.1 14.34 1 54 0 1
#> 106 16.67 1 49 1 0
#> 180.2 14.82 1 37 0 0
#> 13.2 14.34 1 54 0 1
#> 86.1 23.81 1 58 0 1
#> 184.1 17.77 1 38 0 0
#> 78.1 23.88 1 43 0 0
#> 181 16.46 1 45 0 1
#> 70 7.38 1 30 1 0
#> 183.2 9.24 1 67 1 0
#> 113 22.86 1 34 0 0
#> 199 19.81 1 NA 0 1
#> 16.1 8.71 1 71 0 1
#> 50 10.02 1 NA 1 0
#> 100.1 16.07 1 60 0 0
#> 127.2 3.53 1 62 0 1
#> 68.1 20.62 1 44 0 0
#> 18 15.21 1 49 1 0
#> 110.1 17.56 1 65 0 1
#> 88 18.37 1 47 0 0
#> 79.2 16.23 1 54 1 0
#> 189 10.51 1 NA 1 0
#> 96.1 14.54 1 33 0 1
#> 169.2 22.41 1 46 0 0
#> 37.1 12.52 1 57 1 0
#> 111.1 17.45 1 47 0 1
#> 157.1 15.10 1 47 0 0
#> 159.1 10.55 1 50 0 1
#> 6.1 15.64 1 39 0 0
#> 184.2 17.77 1 38 0 0
#> 57 14.46 1 45 0 1
#> 125 15.65 1 67 1 0
#> 41 18.02 1 40 1 0
#> 168.2 23.72 1 70 0 0
#> 70.1 7.38 1 30 1 0
#> 125.1 15.65 1 67 1 0
#> 96.2 14.54 1 33 0 1
#> 101.1 9.97 1 10 0 1
#> 101.2 9.97 1 10 0 1
#> 192 16.44 1 31 1 0
#> 106.1 16.67 1 49 1 0
#> 66 22.13 1 53 0 0
#> 181.1 16.46 1 45 0 1
#> 114 13.68 1 NA 0 0
#> 182 24.00 0 35 0 0
#> 47 24.00 0 38 0 1
#> 147 24.00 0 76 1 0
#> 200 24.00 0 64 0 0
#> 80 24.00 0 41 0 0
#> 20 24.00 0 46 1 0
#> 182.1 24.00 0 35 0 0
#> 137 24.00 0 45 1 0
#> 163 24.00 0 66 0 0
#> 141 24.00 0 44 1 0
#> 44 24.00 0 56 0 0
#> 112 24.00 0 61 0 0
#> 74 24.00 0 43 0 1
#> 162 24.00 0 51 0 0
#> 28 24.00 0 67 1 0
#> 173 24.00 0 19 0 1
#> 142 24.00 0 53 0 0
#> 137.1 24.00 0 45 1 0
#> 46 24.00 0 71 0 0
#> 82 24.00 0 34 0 0
#> 156 24.00 0 50 1 0
#> 109 24.00 0 48 0 0
#> 34 24.00 0 36 0 0
#> 11 24.00 0 42 0 1
#> 135 24.00 0 58 1 0
#> 198 24.00 0 66 0 1
#> 95 24.00 0 68 0 1
#> 193 24.00 0 45 0 1
#> 200.1 24.00 0 64 0 0
#> 74.1 24.00 0 43 0 1
#> 103 24.00 0 56 1 0
#> 22 24.00 0 52 1 0
#> 115 24.00 0 NA 1 0
#> 152 24.00 0 36 0 1
#> 147.1 24.00 0 76 1 0
#> 11.1 24.00 0 42 0 1
#> 165 24.00 0 47 0 0
#> 38 24.00 0 31 1 0
#> 75 24.00 0 21 1 0
#> 112.1 24.00 0 61 0 0
#> 131 24.00 0 66 0 0
#> 120 24.00 0 68 0 1
#> 3 24.00 0 31 1 0
#> 135.1 24.00 0 58 1 0
#> 178 24.00 0 52 1 0
#> 53 24.00 0 32 0 1
#> 132 24.00 0 55 0 0
#> 95.1 24.00 0 68 0 1
#> 132.1 24.00 0 55 0 0
#> 34.1 24.00 0 36 0 0
#> 48 24.00 0 31 1 0
#> 193.1 24.00 0 45 0 1
#> 98 24.00 0 34 1 0
#> 162.1 24.00 0 51 0 0
#> 196 24.00 0 19 0 0
#> 151 24.00 0 42 0 0
#> 144 24.00 0 28 0 1
#> 122 24.00 0 66 0 0
#> 94 24.00 0 51 0 1
#> 120.1 24.00 0 68 0 1
#> 27 24.00 0 63 1 0
#> 186 24.00 0 45 1 0
#> 120.2 24.00 0 68 0 1
#> 182.2 24.00 0 35 0 0
#> 12 24.00 0 63 0 0
#> 161 24.00 0 45 0 0
#> 174 24.00 0 49 1 0
#> 174.1 24.00 0 49 1 0
#> 198.1 24.00 0 66 0 1
#> 146 24.00 0 63 1 0
#> 173.1 24.00 0 19 0 1
#> 116 24.00 0 58 0 1
#> 67 24.00 0 25 0 0
#> 20.1 24.00 0 46 1 0
#> 144.1 24.00 0 28 0 1
#> 54 24.00 0 53 1 0
#> 21 24.00 0 47 0 0
#> 148 24.00 0 61 1 0
#> 131.1 24.00 0 66 0 0
#> 22.1 24.00 0 52 1 0
#> 48.1 24.00 0 31 1 0
#> 173.2 24.00 0 19 0 1
#> 191 24.00 0 60 0 1
#> 176 24.00 0 43 0 1
#> 172 24.00 0 41 0 0
#> 72 24.00 0 40 0 1
#> 121 24.00 0 57 1 0
#> 46.1 24.00 0 71 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.0273 NA NA NA
#> 2 age, Cure model 0.00294 NA NA NA
#> 3 grade_ii, Cure model -0.248 NA NA NA
#> 4 grade_iii, Cure model 0.289 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0220 NA NA NA
#> 2 grade_ii, Survival model 0.914 NA NA NA
#> 3 grade_iii, Survival model 0.601 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.027312 0.002938 -0.247765 0.288922
#>
#> Degrees of Freedom: 192 Total (i.e. Null); 189 Residual
#> Null Deviance: 265.7
#> Residual Deviance: 263.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.027312012 0.002938357 -0.247765118 0.288922374
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.02203607 0.91404871 0.60067231
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 3.224627e-04 7.676562e-02 3.759178e-01 4.470905e-02 9.539520e-01
#> [6] 3.317820e-01 3.590734e-02 4.106640e-01 2.444932e-05 8.334952e-01
#> [11] 1.384248e-01 1.714832e-01 4.015088e-02 1.566886e-02 2.449003e-02
#> [16] 6.026270e-01 7.302561e-01 6.578995e-01 1.088108e-01 4.768975e-03
#> [21] 5.755780e-01 7.600735e-01 3.535534e-01 6.722084e-01 2.805895e-02
#> [26] 4.963575e-02 2.331945e-01 8.187474e-01 8.779580e-01 8.923338e-02
#> [31] 9.848984e-04 7.752530e-01 1.714832e-01 3.759178e-01 2.151461e-01
#> [36] 4.963575e-02 5.226475e-01 5.226475e-01 9.539520e-01 5.490277e-01
#> [41] 2.604879e-01 1.884523e-01 4.768975e-03 2.331945e-01 6.483495e-02
#> [46] 1.566886e-02 2.800371e-01 5.623977e-01 9.387480e-01 4.844119e-01
#> [51] 9.848984e-04 1.233037e-01 7.010672e-01 4.351710e-01 5.755780e-01
#> [56] 6.865583e-01 6.300325e-01 7.302561e-01 6.300325e-01 8.334952e-01
#> [61] 1.274972e-02 3.105508e-01 4.963575e-02 1.465801e-01 4.106640e-01
#> [66] 1.566886e-02 4.844119e-01 1.549427e-01 3.759178e-01 4.844119e-01
#> [71] 3.224627e-04 8.923338e-02 2.444932e-05 1.973137e-01 9.084993e-01
#> [76] 8.334952e-01 3.380267e-03 8.779580e-01 2.604879e-01 9.539520e-01
#> [81] 2.805895e-02 3.426413e-01 1.088108e-01 7.063788e-02 2.331945e-01
#> [86] 4.351710e-01 4.768975e-03 6.026270e-01 1.233037e-01 3.535534e-01
#> [91] 7.010672e-01 3.105508e-01 8.923338e-02 4.717728e-01 2.901251e-01
#> [96] 8.300715e-02 9.848984e-04 9.084993e-01 2.901251e-01 4.351710e-01
#> [101] 7.752530e-01 7.752530e-01 2.151461e-01 1.549427e-01 1.010702e-02
#> [106] 1.973137e-01 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [186] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [191] 0.000000e+00 0.000000e+00 0.000000e+00
#>
#> $Time
#> 86 108 180 105 127 39 128 133 78 183 30 171 166
#> 23.81 18.29 14.82 19.75 3.53 15.59 20.35 14.65 23.88 9.24 17.43 16.57 19.98
#> 139 36 37 10 56 110 169 177 145 157 49 68 76
#> 21.49 21.19 12.52 10.53 12.21 17.56 22.41 12.53 10.07 15.10 12.19 20.62 19.22
#> 79 187 16 184 168 101 171.1 180.1 85 76.1 155 155.1 127.1
#> 16.23 9.92 8.71 17.77 23.72 9.97 16.57 14.82 16.44 19.22 13.08 13.08 3.53
#> 123 100 130 169.1 79.1 97 139.1 26 154 25 13 168.1 111
#> 13.00 16.07 16.47 22.41 16.23 19.14 21.49 15.77 12.63 6.32 14.34 23.72 17.45
#> 159 96 177.1 43 42 10.1 42.1 183.1 197 6 76.2 45 133.1
#> 10.55 14.54 12.53 12.10 12.43 10.53 12.43 9.24 21.60 15.64 19.22 17.42 14.65
#> 139.2 13.1 106 180.2 13.2 86.1 184.1 78.1 181 70 183.2 113 16.1
#> 21.49 14.34 16.67 14.82 14.34 23.81 17.77 23.88 16.46 7.38 9.24 22.86 8.71
#> 100.1 127.2 68.1 18 110.1 88 79.2 96.1 169.2 37.1 111.1 157.1 159.1
#> 16.07 3.53 20.62 15.21 17.56 18.37 16.23 14.54 22.41 12.52 17.45 15.10 10.55
#> 6.1 184.2 57 125 41 168.2 70.1 125.1 96.2 101.1 101.2 192 106.1
#> 15.64 17.77 14.46 15.65 18.02 23.72 7.38 15.65 14.54 9.97 9.97 16.44 16.67
#> 66 181.1 182 47 147 200 80 20 182.1 137 163 141 44
#> 22.13 16.46 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 112 74 162 28 173 142 137.1 46 82 156 109 34 11
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135 198 95 193 200.1 74.1 103 22 152 147.1 11.1 165 38
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75 112.1 131 120 3 135.1 178 53 132 95.1 132.1 34.1 48
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193.1 98 162.1 196 151 144 122 94 120.1 27 186 120.2 182.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12 161 174 174.1 198.1 146 173.1 116 67 20.1 144.1 54 21
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148 131.1 22.1 48.1 173.2 191 176 172 72 121 46.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[70]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.005012427 0.545997676 0.184949088
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.54496234 0.01209615 -0.32128533
#> grade_iii, Cure model
#> 0.89603200
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 24 23.89 1 38 0 0
#> 166 19.98 1 48 0 0
#> 108 18.29 1 39 0 1
#> 114 13.68 1 NA 0 0
#> 101 9.97 1 10 0 1
#> 170 19.54 1 43 0 1
#> 158 20.14 1 74 1 0
#> 45 17.42 1 54 0 1
#> 100 16.07 1 60 0 0
#> 175 21.91 1 43 0 0
#> 100.1 16.07 1 60 0 0
#> 130 16.47 1 53 0 1
#> 25 6.32 1 34 1 0
#> 133 14.65 1 57 0 0
#> 199 19.81 1 NA 0 1
#> 18 15.21 1 49 1 0
#> 110 17.56 1 65 0 1
#> 167 15.55 1 56 1 0
#> 136 21.83 1 43 0 1
#> 85 16.44 1 36 0 0
#> 188 16.16 1 46 0 1
#> 194 22.40 1 38 0 1
#> 130.1 16.47 1 53 0 1
#> 69 23.23 1 25 0 1
#> 16 8.71 1 71 0 1
#> 29 15.45 1 68 1 0
#> 86 23.81 1 58 0 1
#> 79 16.23 1 54 1 0
#> 175.1 21.91 1 43 0 0
#> 92 22.92 1 47 0 1
#> 150 20.33 1 48 0 0
#> 179 18.63 1 42 0 0
#> 117 17.46 1 26 0 1
#> 43 12.10 1 61 0 1
#> 107 11.18 1 54 1 0
#> 60 13.15 1 38 1 0
#> 76 19.22 1 54 0 1
#> 68 20.62 1 44 0 0
#> 13 14.34 1 54 0 1
#> 125 15.65 1 67 1 0
#> 56 12.21 1 60 0 0
#> 63 22.77 1 31 1 0
#> 139 21.49 1 63 1 0
#> 149 8.37 1 33 1 0
#> 97 19.14 1 65 0 1
#> 68.1 20.62 1 44 0 0
#> 125.1 15.65 1 67 1 0
#> 52 10.42 1 52 0 1
#> 123 13.00 1 44 1 0
#> 195 11.76 1 NA 1 0
#> 30 17.43 1 78 0 0
#> 130.2 16.47 1 53 0 1
#> 57 14.46 1 45 0 1
#> 181 16.46 1 45 0 1
#> 97.1 19.14 1 65 0 1
#> 55 19.34 1 69 0 1
#> 15 22.68 1 48 0 0
#> 13.1 14.34 1 54 0 1
#> 111 17.45 1 47 0 1
#> 76.1 19.22 1 54 0 1
#> 69.1 23.23 1 25 0 1
#> 170.1 19.54 1 43 0 1
#> 81 14.06 1 34 0 0
#> 140 12.68 1 59 1 0
#> 99 21.19 1 38 0 1
#> 177 12.53 1 75 0 0
#> 101.1 9.97 1 10 0 1
#> 40 18.00 1 28 1 0
#> 81.1 14.06 1 34 0 0
#> 97.2 19.14 1 65 0 1
#> 24.1 23.89 1 38 0 0
#> 13.2 14.34 1 54 0 1
#> 68.2 20.62 1 44 0 0
#> 139.1 21.49 1 63 1 0
#> 60.1 13.15 1 38 1 0
#> 184 17.77 1 38 0 0
#> 60.2 13.15 1 38 1 0
#> 60.3 13.15 1 38 1 0
#> 145 10.07 1 65 1 0
#> 124 9.73 1 NA 1 0
#> 168 23.72 1 70 0 0
#> 183 9.24 1 67 1 0
#> 8 18.43 1 32 0 0
#> 56.1 12.21 1 60 0 0
#> 97.3 19.14 1 65 0 1
#> 60.4 13.15 1 38 1 0
#> 177.1 12.53 1 75 0 0
#> 69.2 23.23 1 25 0 1
#> 184.1 17.77 1 38 0 0
#> 106 16.67 1 49 1 0
#> 164 23.60 1 76 0 1
#> 159 10.55 1 50 0 1
#> 93 10.33 1 52 0 1
#> 117.1 17.46 1 26 0 1
#> 81.2 14.06 1 34 0 0
#> 189 10.51 1 NA 1 0
#> 134 17.81 1 47 1 0
#> 57.1 14.46 1 45 0 1
#> 114.1 13.68 1 NA 0 0
#> 129 23.41 1 53 1 0
#> 15.1 22.68 1 48 0 0
#> 99.1 21.19 1 38 0 1
#> 166.1 19.98 1 48 0 0
#> 76.2 19.22 1 54 0 1
#> 41 18.02 1 40 1 0
#> 8.1 18.43 1 32 0 0
#> 199.1 19.81 1 NA 0 1
#> 177.2 12.53 1 75 0 0
#> 139.2 21.49 1 63 1 0
#> 23 16.92 1 61 0 0
#> 181.1 16.46 1 45 0 1
#> 77 7.27 1 67 0 1
#> 191 24.00 0 60 0 1
#> 132 24.00 0 55 0 0
#> 147 24.00 0 76 1 0
#> 17 24.00 0 38 0 1
#> 146 24.00 0 63 1 0
#> 112 24.00 0 61 0 0
#> 22 24.00 0 52 1 0
#> 109 24.00 0 48 0 0
#> 141 24.00 0 44 1 0
#> 178 24.00 0 52 1 0
#> 162 24.00 0 51 0 0
#> 102 24.00 0 49 0 0
#> 120 24.00 0 68 0 1
#> 64 24.00 0 43 0 0
#> 84 24.00 0 39 0 1
#> 156 24.00 0 50 1 0
#> 65 24.00 0 57 1 0
#> 200 24.00 0 64 0 0
#> 151 24.00 0 42 0 0
#> 46 24.00 0 71 0 0
#> 19 24.00 0 57 0 1
#> 72 24.00 0 40 0 1
#> 47 24.00 0 38 0 1
#> 20 24.00 0 46 1 0
#> 98 24.00 0 34 1 0
#> 112.1 24.00 0 61 0 0
#> 151.1 24.00 0 42 0 0
#> 20.1 24.00 0 46 1 0
#> 156.1 24.00 0 50 1 0
#> 71 24.00 0 51 0 0
#> 138 24.00 0 44 1 0
#> 28 24.00 0 67 1 0
#> 82 24.00 0 34 0 0
#> 119 24.00 0 17 0 0
#> 172 24.00 0 41 0 0
#> 17.1 24.00 0 38 0 1
#> 161 24.00 0 45 0 0
#> 112.2 24.00 0 61 0 0
#> 191.1 24.00 0 60 0 1
#> 185 24.00 0 44 1 0
#> 141.1 24.00 0 44 1 0
#> 22.1 24.00 0 52 1 0
#> 102.1 24.00 0 49 0 0
#> 152 24.00 0 36 0 1
#> 138.1 24.00 0 44 1 0
#> 173 24.00 0 19 0 1
#> 120.1 24.00 0 68 0 1
#> 48 24.00 0 31 1 0
#> 22.2 24.00 0 52 1 0
#> 28.1 24.00 0 67 1 0
#> 22.3 24.00 0 52 1 0
#> 119.1 24.00 0 17 0 0
#> 104 24.00 0 50 1 0
#> 82.1 24.00 0 34 0 0
#> 146.1 24.00 0 63 1 0
#> 38 24.00 0 31 1 0
#> 138.2 24.00 0 44 1 0
#> 135 24.00 0 58 1 0
#> 115 24.00 0 NA 1 0
#> 54 24.00 0 53 1 0
#> 119.2 24.00 0 17 0 0
#> 19.1 24.00 0 57 0 1
#> 20.2 24.00 0 46 1 0
#> 172.1 24.00 0 41 0 0
#> 115.1 24.00 0 NA 1 0
#> 191.2 24.00 0 60 0 1
#> 53 24.00 0 32 0 1
#> 82.2 24.00 0 34 0 0
#> 31 24.00 0 36 0 1
#> 182 24.00 0 35 0 0
#> 126 24.00 0 48 0 0
#> 73 24.00 0 NA 0 1
#> 28.2 24.00 0 67 1 0
#> 126.1 24.00 0 48 0 0
#> 17.2 24.00 0 38 0 1
#> 144 24.00 0 28 0 1
#> 22.4 24.00 0 52 1 0
#> 104.1 24.00 0 50 1 0
#> 126.2 24.00 0 48 0 0
#> 109.1 24.00 0 48 0 0
#> 118 24.00 0 44 1 0
#> 142 24.00 0 53 0 0
#> 54.1 24.00 0 53 1 0
#> 121 24.00 0 57 1 0
#> 71.1 24.00 0 51 0 0
#> 112.3 24.00 0 61 0 0
#> 9 24.00 0 31 1 0
#> 27 24.00 0 63 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.545 NA NA NA
#> 2 age, Cure model 0.0121 NA NA NA
#> 3 grade_ii, Cure model -0.321 NA NA NA
#> 4 grade_iii, Cure model 0.896 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00501 NA NA NA
#> 2 grade_ii, Survival model 0.546 NA NA NA
#> 3 grade_iii, Survival model 0.185 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.5450 0.0121 -0.3213 0.8960
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 261.3
#> Residual Deviance: 249.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.54496234 0.01209615 -0.32128533 0.89603200
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.005012427 0.545997676 0.184949088
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.03912552 0.43079556 0.56610586 0.95896290 0.45031325 0.42079908
#> [7] 0.65584266 0.73877237 0.28856403 0.73877237 0.67924438 0.99422551
#> [13] 0.78814802 0.78130458 0.61595445 0.76738215 0.31411520 0.71659452
#> [19] 0.73143717 0.27520206 0.67924438 0.17582053 0.97671306 0.77438802
#> [25] 0.08941993 0.72406387 0.28856403 0.21938244 0.41043284 0.54018201
#> [31] 0.62404493 0.92266099 0.92879478 0.84803412 0.47894033 0.37990867
#> [37] 0.80844410 0.75326945 0.91038266 0.23442787 0.32690029 0.98258244
#> [43] 0.50601576 0.37990867 0.75326945 0.94093936 0.87938235 0.64792908
#> [49] 0.67924438 0.79497187 0.70170313 0.50601576 0.46942316 0.24855240
#> [55] 0.80844410 0.63996899 0.47894033 0.17582053 0.45031325 0.82828305
#> [61] 0.88569077 0.35885432 0.89194042 0.95896290 0.58318085 0.82828305
#> [67] 0.50601576 0.03912552 0.80844410 0.37990867 0.32690029 0.84803412
#> [73] 0.59973873 0.84803412 0.84803412 0.95299718 0.11461292 0.97081826
#> [79] 0.54890089 0.91038266 0.50601576 0.84803412 0.89194042 0.17582053
#> [85] 0.59973873 0.67152722 0.13770025 0.93487784 0.94697904 0.62404493
#> [91] 0.82828305 0.59152843 0.79497187 0.15818645 0.24855240 0.35885432
#> [97] 0.43079556 0.47894033 0.57471371 0.54890089 0.89194042 0.32690029
#> [103] 0.66370151 0.70170313 0.98841569 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 24 166 108 101 170 158 45 100 175 100.1 130 25 133
#> 23.89 19.98 18.29 9.97 19.54 20.14 17.42 16.07 21.91 16.07 16.47 6.32 14.65
#> 18 110 167 136 85 188 194 130.1 69 16 29 86 79
#> 15.21 17.56 15.55 21.83 16.44 16.16 22.40 16.47 23.23 8.71 15.45 23.81 16.23
#> 175.1 92 150 179 117 43 107 60 76 68 13 125 56
#> 21.91 22.92 20.33 18.63 17.46 12.10 11.18 13.15 19.22 20.62 14.34 15.65 12.21
#> 63 139 149 97 68.1 125.1 52 123 30 130.2 57 181 97.1
#> 22.77 21.49 8.37 19.14 20.62 15.65 10.42 13.00 17.43 16.47 14.46 16.46 19.14
#> 55 15 13.1 111 76.1 69.1 170.1 81 140 99 177 101.1 40
#> 19.34 22.68 14.34 17.45 19.22 23.23 19.54 14.06 12.68 21.19 12.53 9.97 18.00
#> 81.1 97.2 24.1 13.2 68.2 139.1 60.1 184 60.2 60.3 145 168 183
#> 14.06 19.14 23.89 14.34 20.62 21.49 13.15 17.77 13.15 13.15 10.07 23.72 9.24
#> 8 56.1 97.3 60.4 177.1 69.2 184.1 106 164 159 93 117.1 81.2
#> 18.43 12.21 19.14 13.15 12.53 23.23 17.77 16.67 23.60 10.55 10.33 17.46 14.06
#> 134 57.1 129 15.1 99.1 166.1 76.2 41 8.1 177.2 139.2 23 181.1
#> 17.81 14.46 23.41 22.68 21.19 19.98 19.22 18.02 18.43 12.53 21.49 16.92 16.46
#> 77 191 132 147 17 146 112 22 109 141 178 162 102
#> 7.27 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120 64 84 156 65 200 151 46 19 72 47 20 98
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 112.1 151.1 20.1 156.1 71 138 28 82 119 172 17.1 161 112.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 191.1 185 141.1 22.1 102.1 152 138.1 173 120.1 48 22.2 28.1 22.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 119.1 104 82.1 146.1 38 138.2 135 54 119.2 19.1 20.2 172.1 191.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53 82.2 31 182 126 28.2 126.1 17.2 144 22.4 104.1 126.2 109.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 118 142 54.1 121 71.1 112.3 9 27
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[71]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.005684939 0.366522224 0.269338406
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.208776273 -0.003806256 -0.218432444
#> grade_iii, Cure model
#> 0.688377162
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 106 16.67 1 49 1 0
#> 59 10.16 1 NA 1 0
#> 25 6.32 1 34 1 0
#> 32 20.90 1 37 1 0
#> 180 14.82 1 37 0 0
#> 168 23.72 1 70 0 0
#> 96 14.54 1 33 0 1
#> 153 21.33 1 55 1 0
#> 55 19.34 1 69 0 1
#> 140 12.68 1 59 1 0
#> 68 20.62 1 44 0 0
#> 180.1 14.82 1 37 0 0
#> 101 9.97 1 10 0 1
#> 157 15.10 1 47 0 0
#> 168.1 23.72 1 70 0 0
#> 184 17.77 1 38 0 0
#> 179 18.63 1 42 0 0
#> 76 19.22 1 54 0 1
#> 153.1 21.33 1 55 1 0
#> 168.2 23.72 1 70 0 0
#> 129 23.41 1 53 1 0
#> 179.1 18.63 1 42 0 0
#> 181 16.46 1 45 0 1
#> 97 19.14 1 65 0 1
#> 6 15.64 1 39 0 0
#> 155 13.08 1 26 0 0
#> 171 16.57 1 41 0 1
#> 188 16.16 1 46 0 1
#> 188.1 16.16 1 46 0 1
#> 130 16.47 1 53 0 1
#> 76.1 19.22 1 54 0 1
#> 168.3 23.72 1 70 0 0
#> 130.1 16.47 1 53 0 1
#> 6.1 15.64 1 39 0 0
#> 18 15.21 1 49 1 0
#> 105 19.75 1 60 0 0
#> 113 22.86 1 34 0 0
#> 4 17.64 1 NA 0 1
#> 150 20.33 1 48 0 0
#> 124 9.73 1 NA 1 0
#> 167 15.55 1 56 1 0
#> 159 10.55 1 50 0 1
#> 177 12.53 1 75 0 0
#> 69 23.23 1 25 0 1
#> 190 20.81 1 42 1 0
#> 85 16.44 1 36 0 0
#> 96.1 14.54 1 33 0 1
#> 114 13.68 1 NA 0 0
#> 150.1 20.33 1 48 0 0
#> 199 19.81 1 NA 0 1
#> 15 22.68 1 48 0 0
#> 36 21.19 1 48 0 1
#> 86 23.81 1 58 0 1
#> 70 7.38 1 30 1 0
#> 63 22.77 1 31 1 0
#> 111 17.45 1 47 0 1
#> 92 22.92 1 47 0 1
#> 188.2 16.16 1 46 0 1
#> 180.2 14.82 1 37 0 0
#> 5 16.43 1 51 0 1
#> 107 11.18 1 54 1 0
#> 8 18.43 1 32 0 0
#> 171.1 16.57 1 41 0 1
#> 85.1 16.44 1 36 0 0
#> 89 11.44 1 NA 0 0
#> 181.1 16.46 1 45 0 1
#> 59.1 10.16 1 NA 1 0
#> 150.2 20.33 1 48 0 0
#> 37 12.52 1 57 1 0
#> 169 22.41 1 46 0 0
#> 114.1 13.68 1 NA 0 0
#> 128 20.35 1 35 0 1
#> 69.1 23.23 1 25 0 1
#> 149 8.37 1 33 1 0
#> 153.2 21.33 1 55 1 0
#> 42 12.43 1 49 0 1
#> 107.1 11.18 1 54 1 0
#> 139 21.49 1 63 1 0
#> 24 23.89 1 38 0 0
#> 179.2 18.63 1 42 0 0
#> 51 18.23 1 83 0 1
#> 69.2 23.23 1 25 0 1
#> 81 14.06 1 34 0 0
#> 43 12.10 1 61 0 1
#> 81.1 14.06 1 34 0 0
#> 149.1 8.37 1 33 1 0
#> 157.1 15.10 1 47 0 0
#> 58 19.34 1 39 0 0
#> 77 7.27 1 67 0 1
#> 125 15.65 1 67 1 0
#> 30 17.43 1 78 0 0
#> 190.1 20.81 1 42 1 0
#> 79 16.23 1 54 1 0
#> 42.1 12.43 1 49 0 1
#> 97.1 19.14 1 65 0 1
#> 153.3 21.33 1 55 1 0
#> 114.2 13.68 1 NA 0 0
#> 192 16.44 1 31 1 0
#> 93 10.33 1 52 0 1
#> 96.2 14.54 1 33 0 1
#> 194 22.40 1 38 0 1
#> 91 5.33 1 61 0 1
#> 58.1 19.34 1 39 0 0
#> 194.1 22.40 1 38 0 1
#> 56 12.21 1 60 0 0
#> 45 17.42 1 54 0 1
#> 52 10.42 1 52 0 1
#> 8.1 18.43 1 32 0 0
#> 76.2 19.22 1 54 0 1
#> 136 21.83 1 43 0 1
#> 23 16.92 1 61 0 0
#> 113.1 22.86 1 34 0 0
#> 174 24.00 0 49 1 0
#> 103 24.00 0 56 1 0
#> 143 24.00 0 51 0 0
#> 35 24.00 0 51 0 0
#> 73 24.00 0 NA 0 1
#> 152 24.00 0 36 0 1
#> 152.1 24.00 0 36 0 1
#> 12 24.00 0 63 0 0
#> 148 24.00 0 61 1 0
#> 34 24.00 0 36 0 0
#> 84 24.00 0 39 0 1
#> 74 24.00 0 43 0 1
#> 193 24.00 0 45 0 1
#> 148.1 24.00 0 61 1 0
#> 193.1 24.00 0 45 0 1
#> 9 24.00 0 31 1 0
#> 9.1 24.00 0 31 1 0
#> 20 24.00 0 46 1 0
#> 46 24.00 0 71 0 0
#> 142 24.00 0 53 0 0
#> 182 24.00 0 35 0 0
#> 118 24.00 0 44 1 0
#> 3 24.00 0 31 1 0
#> 80 24.00 0 41 0 0
#> 172 24.00 0 41 0 0
#> 198 24.00 0 66 0 1
#> 200 24.00 0 64 0 0
#> 48 24.00 0 31 1 0
#> 137 24.00 0 45 1 0
#> 196 24.00 0 19 0 0
#> 161 24.00 0 45 0 0
#> 104 24.00 0 50 1 0
#> 28 24.00 0 67 1 0
#> 151 24.00 0 42 0 0
#> 135 24.00 0 58 1 0
#> 161.1 24.00 0 45 0 0
#> 53 24.00 0 32 0 1
#> 142.1 24.00 0 53 0 0
#> 98 24.00 0 34 1 0
#> 80.1 24.00 0 41 0 0
#> 112 24.00 0 61 0 0
#> 132 24.00 0 55 0 0
#> 35.1 24.00 0 51 0 0
#> 27 24.00 0 63 1 0
#> 64 24.00 0 43 0 0
#> 80.2 24.00 0 41 0 0
#> 53.1 24.00 0 32 0 1
#> 120 24.00 0 68 0 1
#> 33 24.00 0 53 0 0
#> 162 24.00 0 51 0 0
#> 38 24.00 0 31 1 0
#> 33.1 24.00 0 53 0 0
#> 141 24.00 0 44 1 0
#> 95 24.00 0 68 0 1
#> 71 24.00 0 51 0 0
#> 163 24.00 0 66 0 0
#> 131 24.00 0 66 0 0
#> 142.2 24.00 0 53 0 0
#> 53.2 24.00 0 32 0 1
#> 118.1 24.00 0 44 1 0
#> 65 24.00 0 57 1 0
#> 62 24.00 0 71 0 0
#> 147 24.00 0 76 1 0
#> 165 24.00 0 47 0 0
#> 67 24.00 0 25 0 0
#> 7 24.00 0 37 1 0
#> 74.1 24.00 0 43 0 1
#> 46.1 24.00 0 71 0 0
#> 193.2 24.00 0 45 0 1
#> 102 24.00 0 49 0 0
#> 116 24.00 0 58 0 1
#> 7.1 24.00 0 37 1 0
#> 137.1 24.00 0 45 1 0
#> 47 24.00 0 38 0 1
#> 22 24.00 0 52 1 0
#> 2 24.00 0 9 0 0
#> 148.2 24.00 0 61 1 0
#> 19 24.00 0 57 0 1
#> 115 24.00 0 NA 1 0
#> 84.1 24.00 0 39 0 1
#> 142.3 24.00 0 53 0 0
#> 116.1 24.00 0 58 0 1
#> 132.1 24.00 0 55 0 0
#> 3.1 24.00 0 31 1 0
#> 74.2 24.00 0 43 0 1
#> 44 24.00 0 56 0 0
#> 3.2 24.00 0 31 1 0
#> 156 24.00 0 50 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.209 NA NA NA
#> 2 age, Cure model -0.00381 NA NA NA
#> 3 grade_ii, Cure model -0.218 NA NA NA
#> 4 grade_iii, Cure model 0.688 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00568 NA NA NA
#> 2 grade_ii, Survival model 0.367 NA NA NA
#> 3 grade_iii, Survival model 0.269 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.208776 -0.003806 -0.218432 0.688377
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.5
#> Residual Deviance: 254 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.208776273 -0.003806256 -0.218432444 0.688377162
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.005684939 0.366522224 0.269338406
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.492065285 0.979463268 0.225704344 0.712705384 0.021120322 0.743104129
#> [7] 0.181357499 0.308289874 0.804118633 0.252976258 0.712705384 0.928078638
#> [13] 0.692457817 0.021120322 0.441869678 0.383617555 0.336353116 0.181357499
#> [19] 0.021120322 0.052058850 0.383617555 0.542150981 0.364504461 0.652038815
#> [25] 0.793821683 0.502170644 0.612157889 0.612157889 0.522148729 0.336353116
#> [31] 0.021120322 0.522148729 0.652038815 0.682328906 0.298789658 0.096719883
#> [37] 0.271429000 0.672186154 0.896977185 0.814411420 0.062436498 0.234980036
#> [43] 0.562143280 0.743104129 0.271429000 0.124357830 0.216363828 0.011915768
#> [49] 0.958905214 0.114990041 0.451846927 0.087436711 0.612157889 0.712705384
#> [55] 0.591948173 0.876372263 0.412378655 0.502170644 0.562143280 0.542150981
#> [61] 0.271429000 0.824749562 0.133897498 0.262214444 0.062436498 0.938421480
#> [67] 0.181357499 0.835082085 0.876372263 0.171785786 0.003444318 0.383617555
#> [73] 0.431936015 0.062436498 0.773397517 0.865993476 0.773397517 0.938421480
#> [79] 0.692457817 0.308289874 0.969178487 0.641948612 0.461823712 0.234980036
#> [85] 0.602058231 0.835082085 0.364504461 0.181357499 0.562143280 0.917708437
#> [91] 0.743104129 0.143596403 0.989727664 0.308289874 0.143596403 0.855623951
#> [97] 0.471878299 0.907341275 0.412378655 0.336353116 0.162209726 0.481940817
#> [103] 0.096719883 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 106 25 32 180 168 96 153 55 140 68 180.1 101 157
#> 16.67 6.32 20.90 14.82 23.72 14.54 21.33 19.34 12.68 20.62 14.82 9.97 15.10
#> 168.1 184 179 76 153.1 168.2 129 179.1 181 97 6 155 171
#> 23.72 17.77 18.63 19.22 21.33 23.72 23.41 18.63 16.46 19.14 15.64 13.08 16.57
#> 188 188.1 130 76.1 168.3 130.1 6.1 18 105 113 150 167 159
#> 16.16 16.16 16.47 19.22 23.72 16.47 15.64 15.21 19.75 22.86 20.33 15.55 10.55
#> 177 69 190 85 96.1 150.1 15 36 86 70 63 111 92
#> 12.53 23.23 20.81 16.44 14.54 20.33 22.68 21.19 23.81 7.38 22.77 17.45 22.92
#> 188.2 180.2 5 107 8 171.1 85.1 181.1 150.2 37 169 128 69.1
#> 16.16 14.82 16.43 11.18 18.43 16.57 16.44 16.46 20.33 12.52 22.41 20.35 23.23
#> 149 153.2 42 107.1 139 24 179.2 51 69.2 81 43 81.1 149.1
#> 8.37 21.33 12.43 11.18 21.49 23.89 18.63 18.23 23.23 14.06 12.10 14.06 8.37
#> 157.1 58 77 125 30 190.1 79 42.1 97.1 153.3 192 93 96.2
#> 15.10 19.34 7.27 15.65 17.43 20.81 16.23 12.43 19.14 21.33 16.44 10.33 14.54
#> 194 91 58.1 194.1 56 45 52 8.1 76.2 136 23 113.1 174
#> 22.40 5.33 19.34 22.40 12.21 17.42 10.42 18.43 19.22 21.83 16.92 22.86 24.00
#> 103 143 35 152 152.1 12 148 34 84 74 193 148.1 193.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9 9.1 20 46 142 182 118 3 80 172 198 200 48
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137 196 161 104 28 151 135 161.1 53 142.1 98 80.1 112
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 132 35.1 27 64 80.2 53.1 120 33 162 38 33.1 141 95
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71 163 131 142.2 53.2 118.1 65 62 147 165 67 7 74.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 46.1 193.2 102 116 7.1 137.1 47 22 2 148.2 19 84.1 142.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116.1 132.1 3.1 74.2 44 3.2 156
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[72]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.001931335 0.576393588 0.088380657
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.74503621 0.02257081 -0.40393026
#> grade_iii, Cure model
#> 0.01063567
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 77 7.27 1 67 0 1
#> 99 21.19 1 38 0 1
#> 93 10.33 1 52 0 1
#> 179 18.63 1 42 0 0
#> 81 14.06 1 34 0 0
#> 154 12.63 1 20 1 0
#> 76 19.22 1 54 0 1
#> 101 9.97 1 10 0 1
#> 43 12.10 1 61 0 1
#> 105 19.75 1 60 0 0
#> 15 22.68 1 48 0 0
#> 129 23.41 1 53 1 0
#> 85 16.44 1 36 0 0
#> 157 15.10 1 47 0 0
#> 183 9.24 1 67 1 0
#> 69 23.23 1 25 0 1
#> 113 22.86 1 34 0 0
#> 39 15.59 1 37 0 1
#> 113.1 22.86 1 34 0 0
#> 56 12.21 1 60 0 0
#> 92 22.92 1 47 0 1
#> 100 16.07 1 60 0 0
#> 88 18.37 1 47 0 0
#> 81.1 14.06 1 34 0 0
#> 184 17.77 1 38 0 0
#> 127 3.53 1 62 0 1
#> 96 14.54 1 33 0 1
#> 88.1 18.37 1 47 0 0
#> 170 19.54 1 43 0 1
#> 97 19.14 1 65 0 1
#> 170.1 19.54 1 43 0 1
#> 168 23.72 1 70 0 0
#> 179.1 18.63 1 42 0 0
#> 76.1 19.22 1 54 0 1
#> 110 17.56 1 65 0 1
#> 57 14.46 1 45 0 1
#> 56.1 12.21 1 60 0 0
#> 177 12.53 1 75 0 0
#> 14 12.89 1 21 0 0
#> 190 20.81 1 42 1 0
#> 41 18.02 1 40 1 0
#> 187 9.92 1 39 1 0
#> 145 10.07 1 65 1 0
#> 99.1 21.19 1 38 0 1
#> 8 18.43 1 32 0 0
#> 86 23.81 1 58 0 1
#> 158 20.14 1 74 1 0
#> 66 22.13 1 53 0 0
#> 8.1 18.43 1 32 0 0
#> 85.1 16.44 1 36 0 0
#> 5 16.43 1 51 0 1
#> 78 23.88 1 43 0 0
#> 14.1 12.89 1 21 0 0
#> 66.1 22.13 1 53 0 0
#> 111 17.45 1 47 0 1
#> 199 19.81 1 NA 0 1
#> 153 21.33 1 55 1 0
#> 23 16.92 1 61 0 0
#> 114 13.68 1 NA 0 0
#> 77.1 7.27 1 67 0 1
#> 70 7.38 1 30 1 0
#> 154.1 12.63 1 20 1 0
#> 51 18.23 1 83 0 1
#> 30 17.43 1 78 0 0
#> 107 11.18 1 54 1 0
#> 15.1 22.68 1 48 0 0
#> 128 20.35 1 35 0 1
#> 100.1 16.07 1 60 0 0
#> 43.1 12.10 1 61 0 1
#> 100.2 16.07 1 60 0 0
#> 164 23.60 1 76 0 1
#> 4 17.64 1 NA 0 1
#> 92.1 22.92 1 47 0 1
#> 113.2 22.86 1 34 0 0
#> 110.1 17.56 1 65 0 1
#> 8.2 18.43 1 32 0 0
#> 188 16.16 1 46 0 1
#> 76.2 19.22 1 54 0 1
#> 170.2 19.54 1 43 0 1
#> 56.2 12.21 1 60 0 0
#> 130 16.47 1 53 0 1
#> 81.2 14.06 1 34 0 0
#> 110.2 17.56 1 65 0 1
#> 159 10.55 1 50 0 1
#> 134 17.81 1 47 1 0
#> 18 15.21 1 49 1 0
#> 134.1 17.81 1 47 1 0
#> 106 16.67 1 49 1 0
#> 106.1 16.67 1 49 1 0
#> 107.1 11.18 1 54 1 0
#> 51.1 18.23 1 83 0 1
#> 166 19.98 1 48 0 0
#> 133 14.65 1 57 0 0
#> 130.1 16.47 1 53 0 1
#> 4.1 17.64 1 NA 0 1
#> 26 15.77 1 49 0 1
#> 171 16.57 1 41 0 1
#> 40 18.00 1 28 1 0
#> 79 16.23 1 54 1 0
#> 49 12.19 1 48 1 0
#> 57.1 14.46 1 45 0 1
#> 123 13.00 1 44 1 0
#> 183.1 9.24 1 67 1 0
#> 97.1 19.14 1 65 0 1
#> 153.1 21.33 1 55 1 0
#> 66.2 22.13 1 53 0 0
#> 86.1 23.81 1 58 0 1
#> 195 11.76 1 NA 1 0
#> 30.1 17.43 1 78 0 0
#> 78.1 23.88 1 43 0 0
#> 86.2 23.81 1 58 0 1
#> 41.1 18.02 1 40 1 0
#> 119 24.00 0 17 0 0
#> 144 24.00 0 28 0 1
#> 138 24.00 0 44 1 0
#> 84 24.00 0 39 0 1
#> 19 24.00 0 57 0 1
#> 132 24.00 0 55 0 0
#> 74 24.00 0 43 0 1
#> 62 24.00 0 71 0 0
#> 7 24.00 0 37 1 0
#> 176 24.00 0 43 0 1
#> 72 24.00 0 40 0 1
#> 152 24.00 0 36 0 1
#> 185 24.00 0 44 1 0
#> 173 24.00 0 19 0 1
#> 152.1 24.00 0 36 0 1
#> 19.1 24.00 0 57 0 1
#> 46 24.00 0 71 0 0
#> 64 24.00 0 43 0 0
#> 119.1 24.00 0 17 0 0
#> 9 24.00 0 31 1 0
#> 75 24.00 0 21 1 0
#> 1 24.00 0 23 1 0
#> 120 24.00 0 68 0 1
#> 198 24.00 0 66 0 1
#> 64.1 24.00 0 43 0 0
#> 112 24.00 0 61 0 0
#> 102 24.00 0 49 0 0
#> 178 24.00 0 52 1 0
#> 185.1 24.00 0 44 1 0
#> 115 24.00 0 NA 1 0
#> 176.1 24.00 0 43 0 1
#> 11 24.00 0 42 0 1
#> 22 24.00 0 52 1 0
#> 186 24.00 0 45 1 0
#> 198.1 24.00 0 66 0 1
#> 27 24.00 0 63 1 0
#> 135 24.00 0 58 1 0
#> 72.1 24.00 0 40 0 1
#> 19.2 24.00 0 57 0 1
#> 11.1 24.00 0 42 0 1
#> 80 24.00 0 41 0 0
#> 34 24.00 0 36 0 0
#> 31 24.00 0 36 0 1
#> 48 24.00 0 31 1 0
#> 83 24.00 0 6 0 0
#> 21 24.00 0 47 0 0
#> 126 24.00 0 48 0 0
#> 141 24.00 0 44 1 0
#> 20 24.00 0 46 1 0
#> 119.2 24.00 0 17 0 0
#> 142 24.00 0 53 0 0
#> 137 24.00 0 45 1 0
#> 172 24.00 0 41 0 0
#> 94 24.00 0 51 0 1
#> 84.1 24.00 0 39 0 1
#> 147 24.00 0 76 1 0
#> 138.1 24.00 0 44 1 0
#> 119.3 24.00 0 17 0 0
#> 156 24.00 0 50 1 0
#> 135.1 24.00 0 58 1 0
#> 31.1 24.00 0 36 0 1
#> 64.2 24.00 0 43 0 0
#> 95 24.00 0 68 0 1
#> 27.1 24.00 0 63 1 0
#> 185.2 24.00 0 44 1 0
#> 46.1 24.00 0 71 0 0
#> 75.1 24.00 0 21 1 0
#> 48.1 24.00 0 31 1 0
#> 161 24.00 0 45 0 0
#> 7.1 24.00 0 37 1 0
#> 12 24.00 0 63 0 0
#> 11.2 24.00 0 42 0 1
#> 176.2 24.00 0 43 0 1
#> 142.1 24.00 0 53 0 0
#> 84.2 24.00 0 39 0 1
#> 116 24.00 0 58 0 1
#> 172.1 24.00 0 41 0 0
#> 143 24.00 0 51 0 0
#> 122 24.00 0 66 0 0
#> 2 24.00 0 9 0 0
#> 65 24.00 0 57 1 0
#> 53 24.00 0 32 0 1
#> 75.2 24.00 0 21 1 0
#> 182 24.00 0 35 0 0
#> 54 24.00 0 53 1 0
#> 126.1 24.00 0 48 0 0
#> 193 24.00 0 45 0 1
#> 131 24.00 0 66 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.745 NA NA NA
#> 2 age, Cure model 0.0226 NA NA NA
#> 3 grade_ii, Cure model -0.404 NA NA NA
#> 4 grade_iii, Cure model 0.0106 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00193 NA NA NA
#> 2 grade_ii, Survival model 0.576 NA NA NA
#> 3 grade_iii, Survival model 0.0884 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.74504 0.02257 -0.40393 0.01064
#>
#> Degrees of Freedom: 193 Total (i.e. Null); 190 Residual
#> Null Deviance: 266.9
#> Residual Deviance: 259.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.74503621 0.02257081 -0.40393026 0.01063567
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.001931335 0.576393588 0.088380657
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.97488511 0.22388945 0.91538170 0.36665096 0.75825795 0.81128212
#> [7] 0.31974073 0.93259012 0.87221595 0.28218551 0.15318594 0.08223170
#> [13] 0.61558560 0.71377652 0.94969108 0.09290562 0.12371324 0.69590502
#> [19] 0.12371324 0.83742089 0.10353100 0.66036611 0.41396890 0.75825795
#> [25] 0.49841549 0.99160322 0.73160868 0.41396890 0.29181297 0.34770858
#> [31] 0.29181297 0.05917850 0.36665096 0.31974073 0.50752444 0.74052778
#> [37] 0.83742089 0.82866895 0.79362584 0.24351591 0.45235693 0.94116586
#> [43] 0.92400873 0.22388945 0.38567009 0.03155393 0.26303206 0.17377100
#> [49] 0.38567009 0.61558560 0.63347983 0.01064515 0.79362584 0.17377100
#> [55] 0.53441597 0.20423809 0.56170433 0.97488511 0.96649571 0.81128212
#> [61] 0.43313334 0.54353489 0.88958693 0.15318594 0.25327791 0.66036611
#> [67] 0.87221595 0.66036611 0.07064977 0.10353100 0.12371324 0.50752444
#> [73] 0.38567009 0.65142919 0.31974073 0.29181297 0.83742089 0.59772627
#> [79] 0.75825795 0.50752444 0.90675565 0.48038716 0.70487582 0.48038716
#> [85] 0.57088036 0.57088036 0.88958693 0.43313334 0.27259387 0.72268687
#> [91] 0.59772627 0.68693224 0.58873267 0.47106606 0.64249233 0.86349185
#> [97] 0.74052778 0.78475594 0.94969108 0.34770858 0.20423809 0.17377100
#> [103] 0.03155393 0.54353489 0.01064515 0.03155393 0.45235693 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [193] 0.00000000 0.00000000
#>
#> $Time
#> 77 99 93 179 81 154 76 101 43 105 15 129 85
#> 7.27 21.19 10.33 18.63 14.06 12.63 19.22 9.97 12.10 19.75 22.68 23.41 16.44
#> 157 183 69 113 39 113.1 56 92 100 88 81.1 184 127
#> 15.10 9.24 23.23 22.86 15.59 22.86 12.21 22.92 16.07 18.37 14.06 17.77 3.53
#> 96 88.1 170 97 170.1 168 179.1 76.1 110 57 56.1 177 14
#> 14.54 18.37 19.54 19.14 19.54 23.72 18.63 19.22 17.56 14.46 12.21 12.53 12.89
#> 190 41 187 145 99.1 8 86 158 66 8.1 85.1 5 78
#> 20.81 18.02 9.92 10.07 21.19 18.43 23.81 20.14 22.13 18.43 16.44 16.43 23.88
#> 14.1 66.1 111 153 23 77.1 70 154.1 51 30 107 15.1 128
#> 12.89 22.13 17.45 21.33 16.92 7.27 7.38 12.63 18.23 17.43 11.18 22.68 20.35
#> 100.1 43.1 100.2 164 92.1 113.2 110.1 8.2 188 76.2 170.2 56.2 130
#> 16.07 12.10 16.07 23.60 22.92 22.86 17.56 18.43 16.16 19.22 19.54 12.21 16.47
#> 81.2 110.2 159 134 18 134.1 106 106.1 107.1 51.1 166 133 130.1
#> 14.06 17.56 10.55 17.81 15.21 17.81 16.67 16.67 11.18 18.23 19.98 14.65 16.47
#> 26 171 40 79 49 57.1 123 183.1 97.1 153.1 66.2 86.1 30.1
#> 15.77 16.57 18.00 16.23 12.19 14.46 13.00 9.24 19.14 21.33 22.13 23.81 17.43
#> 78.1 86.2 41.1 119 144 138 84 19 132 74 62 7 176
#> 23.88 23.81 18.02 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72 152 185 173 152.1 19.1 46 64 119.1 9 75 1 120
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 198 64.1 112 102 178 185.1 176.1 11 22 186 198.1 27 135
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72.1 19.2 11.1 80 34 31 48 83 21 126 141 20 119.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142 137 172 94 84.1 147 138.1 119.3 156 135.1 31.1 64.2 95
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 27.1 185.2 46.1 75.1 48.1 161 7.1 12 11.2 176.2 142.1 84.2 116
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172.1 143 122 2 65 53 75.2 182 54 126.1 193 131
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[73]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.01134954 0.37358969 0.12828859
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.3713074986 -0.0009821155 0.2458462510
#> grade_iii, Cure model
#> 1.6236263243
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 192 16.44 1 31 1 0
#> 99 21.19 1 38 0 1
#> 145 10.07 1 65 1 0
#> 36 21.19 1 48 0 1
#> 175 21.91 1 43 0 0
#> 16 8.71 1 71 0 1
#> 117 17.46 1 26 0 1
#> 134 17.81 1 47 1 0
#> 25 6.32 1 34 1 0
#> 57 14.46 1 45 0 1
#> 8 18.43 1 32 0 0
#> 153 21.33 1 55 1 0
#> 113 22.86 1 34 0 0
#> 189 10.51 1 NA 1 0
#> 136 21.83 1 43 0 1
#> 6 15.64 1 39 0 0
#> 99.1 21.19 1 38 0 1
#> 52 10.42 1 52 0 1
#> 39 15.59 1 37 0 1
#> 55 19.34 1 69 0 1
#> 25.1 6.32 1 34 1 0
#> 61 10.12 1 36 0 1
#> 6.1 15.64 1 39 0 0
#> 183 9.24 1 67 1 0
#> 90 20.94 1 50 0 1
#> 140 12.68 1 59 1 0
#> 169 22.41 1 46 0 0
#> 77 7.27 1 67 0 1
#> 99.2 21.19 1 38 0 1
#> 164 23.60 1 76 0 1
#> 45 17.42 1 54 0 1
#> 127 3.53 1 62 0 1
#> 69 23.23 1 25 0 1
#> 32 20.90 1 37 1 0
#> 92 22.92 1 47 0 1
#> 175.1 21.91 1 43 0 0
#> 153.1 21.33 1 55 1 0
#> 111 17.45 1 47 0 1
#> 108 18.29 1 39 0 1
#> 99.3 21.19 1 38 0 1
#> 155 13.08 1 26 0 0
#> 57.1 14.46 1 45 0 1
#> 192.1 16.44 1 31 1 0
#> 39.1 15.59 1 37 0 1
#> 93 10.33 1 52 0 1
#> 150 20.33 1 48 0 0
#> 4 17.64 1 NA 0 1
#> 130 16.47 1 53 0 1
#> 77.1 7.27 1 67 0 1
#> 145.1 10.07 1 65 1 0
#> 32.1 20.90 1 37 1 0
#> 199 19.81 1 NA 0 1
#> 113.1 22.86 1 34 0 0
#> 177 12.53 1 75 0 0
#> 86 23.81 1 58 0 1
#> 96 14.54 1 33 0 1
#> 36.1 21.19 1 48 0 1
#> 100 16.07 1 60 0 0
#> 167 15.55 1 56 1 0
#> 16.1 8.71 1 71 0 1
#> 40 18.00 1 28 1 0
#> 166 19.98 1 48 0 0
#> 105 19.75 1 60 0 0
#> 68 20.62 1 44 0 0
#> 57.2 14.46 1 45 0 1
#> 76 19.22 1 54 0 1
#> 189.1 10.51 1 NA 1 0
#> 52.1 10.42 1 52 0 1
#> 69.1 23.23 1 25 0 1
#> 175.2 21.91 1 43 0 0
#> 85 16.44 1 36 0 0
#> 93.1 10.33 1 52 0 1
#> 92.1 22.92 1 47 0 1
#> 123 13.00 1 44 1 0
#> 106 16.67 1 49 1 0
#> 29 15.45 1 68 1 0
#> 40.1 18.00 1 28 1 0
#> 63 22.77 1 31 1 0
#> 57.3 14.46 1 45 0 1
#> 56 12.21 1 60 0 0
#> 77.2 7.27 1 67 0 1
#> 139 21.49 1 63 1 0
#> 129 23.41 1 53 1 0
#> 89 11.44 1 NA 0 0
#> 91 5.33 1 61 0 1
#> 97 19.14 1 65 0 1
#> 76.1 19.22 1 54 0 1
#> 50 10.02 1 NA 1 0
#> 107 11.18 1 54 1 0
#> 155.1 13.08 1 26 0 0
#> 107.1 11.18 1 54 1 0
#> 58 19.34 1 39 0 0
#> 184 17.77 1 38 0 0
#> 91.1 5.33 1 61 0 1
#> 150.1 20.33 1 48 0 0
#> 40.2 18.00 1 28 1 0
#> 88 18.37 1 47 0 0
#> 114 13.68 1 NA 0 0
#> 51 18.23 1 83 0 1
#> 51.1 18.23 1 83 0 1
#> 88.1 18.37 1 47 0 0
#> 39.2 15.59 1 37 0 1
#> 32.2 20.90 1 37 1 0
#> 10 10.53 1 34 0 0
#> 171 16.57 1 41 0 1
#> 199.1 19.81 1 NA 0 1
#> 97.1 19.14 1 65 0 1
#> 24 23.89 1 38 0 0
#> 181 16.46 1 45 0 1
#> 187 9.92 1 39 1 0
#> 136.1 21.83 1 43 0 1
#> 184.1 17.77 1 38 0 0
#> 118 24.00 0 44 1 0
#> 7 24.00 0 37 1 0
#> 3 24.00 0 31 1 0
#> 47 24.00 0 38 0 1
#> 53 24.00 0 32 0 1
#> 62 24.00 0 71 0 0
#> 38 24.00 0 31 1 0
#> 12 24.00 0 63 0 0
#> 82 24.00 0 34 0 0
#> 12.1 24.00 0 63 0 0
#> 35 24.00 0 51 0 0
#> 118.1 24.00 0 44 1 0
#> 142 24.00 0 53 0 0
#> 112 24.00 0 61 0 0
#> 94 24.00 0 51 0 1
#> 172 24.00 0 41 0 0
#> 98 24.00 0 34 1 0
#> 12.2 24.00 0 63 0 0
#> 27 24.00 0 63 1 0
#> 87 24.00 0 27 0 0
#> 186 24.00 0 45 1 0
#> 151 24.00 0 42 0 0
#> 126 24.00 0 48 0 0
#> 75 24.00 0 21 1 0
#> 161 24.00 0 45 0 0
#> 196 24.00 0 19 0 0
#> 27.1 24.00 0 63 1 0
#> 196.1 24.00 0 19 0 0
#> 62.1 24.00 0 71 0 0
#> 143 24.00 0 51 0 0
#> 62.2 24.00 0 71 0 0
#> 38.1 24.00 0 31 1 0
#> 20 24.00 0 46 1 0
#> 146 24.00 0 63 1 0
#> 120 24.00 0 68 0 1
#> 47.1 24.00 0 38 0 1
#> 95 24.00 0 68 0 1
#> 165 24.00 0 47 0 0
#> 71 24.00 0 51 0 0
#> 44 24.00 0 56 0 0
#> 7.1 24.00 0 37 1 0
#> 109 24.00 0 48 0 0
#> 54 24.00 0 53 1 0
#> 98.1 24.00 0 34 1 0
#> 121 24.00 0 57 1 0
#> 31 24.00 0 36 0 1
#> 34 24.00 0 36 0 0
#> 131 24.00 0 66 0 0
#> 148 24.00 0 61 1 0
#> 38.2 24.00 0 31 1 0
#> 160 24.00 0 31 1 0
#> 46 24.00 0 71 0 0
#> 28 24.00 0 67 1 0
#> 54.1 24.00 0 53 1 0
#> 132 24.00 0 55 0 0
#> 119 24.00 0 17 0 0
#> 178 24.00 0 52 1 0
#> 122 24.00 0 66 0 0
#> 48 24.00 0 31 1 0
#> 103 24.00 0 56 1 0
#> 21 24.00 0 47 0 0
#> 109.1 24.00 0 48 0 0
#> 132.1 24.00 0 55 0 0
#> 119.1 24.00 0 17 0 0
#> 173 24.00 0 19 0 1
#> 135 24.00 0 58 1 0
#> 162 24.00 0 51 0 0
#> 131.1 24.00 0 66 0 0
#> 196.2 24.00 0 19 0 0
#> 94.1 24.00 0 51 0 1
#> 122.1 24.00 0 66 0 0
#> 62.3 24.00 0 71 0 0
#> 75.1 24.00 0 21 1 0
#> 143.1 24.00 0 51 0 0
#> 185 24.00 0 44 1 0
#> 84 24.00 0 39 0 1
#> 95.1 24.00 0 68 0 1
#> 185.1 24.00 0 44 1 0
#> 174 24.00 0 49 1 0
#> 109.2 24.00 0 48 0 0
#> 11 24.00 0 42 0 1
#> 173.1 24.00 0 19 0 1
#> 9 24.00 0 31 1 0
#> 132.2 24.00 0 55 0 0
#> 191 24.00 0 60 0 1
#> 135.1 24.00 0 58 1 0
#> 35.1 24.00 0 51 0 0
#> 53.1 24.00 0 32 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.371 NA NA NA
#> 2 age, Cure model -0.000982 NA NA NA
#> 3 grade_ii, Cure model 0.246 NA NA NA
#> 4 grade_iii, Cure model 1.62 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0113 NA NA NA
#> 2 grade_ii, Survival model 0.374 NA NA NA
#> 3 grade_iii, Survival model 0.128 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.3713075 -0.0009821 0.2458463 1.6236263
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.8
#> Residual Deviance: 243 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.3713074986 -0.0009821155 0.2458462510 1.6236263243
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.01134954 0.37358969 0.12828859
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.76139986 0.44646983 0.93217990 0.44646983 0.34684479 0.95234971
#> [7] 0.71551538 0.69516161 0.97648910 0.83401425 0.63001256 0.42451074
#> [13] 0.28468627 0.38673716 0.78615817 0.44646983 0.90604947 0.79838397
#> [19] 0.58234613 0.97648910 0.92698382 0.78615817 0.94735960 0.50270638
#> [25] 0.87348478 0.33187697 0.96214560 0.44646983 0.16324016 0.72895332
#> [31] 0.99533471 0.21291834 0.51235852 0.25118769 0.34684479 0.42451074
#> [37] 0.72226367 0.65273058 0.44646983 0.85656707 0.83401425 0.76139986
#> [43] 0.79838397 0.91657947 0.54791418 0.74859531 0.96214560 0.93217990
#> [49] 0.51235852 0.28468627 0.87903662 0.12489701 0.82817525 0.44646983
#> [55] 0.77996750 0.81635212 0.95234971 0.67450372 0.56522158 0.57384618
#> [61] 0.53898517 0.83401425 0.59873647 0.90604947 0.21291834 0.34684479
#> [67] 0.76139986 0.91657947 0.25118769 0.86786730 0.73557622 0.82230923
#> [73] 0.67450372 0.31643183 0.83401425 0.88454178 0.96214560 0.41228866
#> [79] 0.19071448 0.98596917 0.61464841 0.59873647 0.89001372 0.85656707
#> [85] 0.89001372 0.58234613 0.70201565 0.98596917 0.54791418 0.67450372
#> [91] 0.63770074 0.66022247 0.66022247 0.63770074 0.79838397 0.51235852
#> [97] 0.90070357 0.74210890 0.61464841 0.06522313 0.75502187 0.94231346
#> [103] 0.38673716 0.70201565 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 192 99 145 36 175 16 117 134 25 57 8 153 113
#> 16.44 21.19 10.07 21.19 21.91 8.71 17.46 17.81 6.32 14.46 18.43 21.33 22.86
#> 136 6 99.1 52 39 55 25.1 61 6.1 183 90 140 169
#> 21.83 15.64 21.19 10.42 15.59 19.34 6.32 10.12 15.64 9.24 20.94 12.68 22.41
#> 77 99.2 164 45 127 69 32 92 175.1 153.1 111 108 99.3
#> 7.27 21.19 23.60 17.42 3.53 23.23 20.90 22.92 21.91 21.33 17.45 18.29 21.19
#> 155 57.1 192.1 39.1 93 150 130 77.1 145.1 32.1 113.1 177 86
#> 13.08 14.46 16.44 15.59 10.33 20.33 16.47 7.27 10.07 20.90 22.86 12.53 23.81
#> 96 36.1 100 167 16.1 40 166 105 68 57.2 76 52.1 69.1
#> 14.54 21.19 16.07 15.55 8.71 18.00 19.98 19.75 20.62 14.46 19.22 10.42 23.23
#> 175.2 85 93.1 92.1 123 106 29 40.1 63 57.3 56 77.2 139
#> 21.91 16.44 10.33 22.92 13.00 16.67 15.45 18.00 22.77 14.46 12.21 7.27 21.49
#> 129 91 97 76.1 107 155.1 107.1 58 184 91.1 150.1 40.2 88
#> 23.41 5.33 19.14 19.22 11.18 13.08 11.18 19.34 17.77 5.33 20.33 18.00 18.37
#> 51 51.1 88.1 39.2 32.2 10 171 97.1 24 181 187 136.1 184.1
#> 18.23 18.23 18.37 15.59 20.90 10.53 16.57 19.14 23.89 16.46 9.92 21.83 17.77
#> 118 7 3 47 53 62 38 12 82 12.1 35 118.1 142
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 112 94 172 98 12.2 27 87 186 151 126 75 161 196
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 27.1 196.1 62.1 143 62.2 38.1 20 146 120 47.1 95 165 71
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44 7.1 109 54 98.1 121 31 34 131 148 38.2 160 46
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28 54.1 132 119 178 122 48 103 21 109.1 132.1 119.1 173
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135 162 131.1 196.2 94.1 122.1 62.3 75.1 143.1 185 84 95.1 185.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174 109.2 11 173.1 9 132.2 191 135.1 35.1 53.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[74]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.009261564 0.352832931 0.103074151
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.68816490 0.01709207 -0.19573155
#> grade_iii, Cure model
#> 0.59847826
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 175 21.91 1 43 0 0
#> 136 21.83 1 43 0 1
#> 18 15.21 1 49 1 0
#> 29 15.45 1 68 1 0
#> 88 18.37 1 47 0 0
#> 16 8.71 1 71 0 1
#> 52 10.42 1 52 0 1
#> 57 14.46 1 45 0 1
#> 124 9.73 1 NA 1 0
#> 129 23.41 1 53 1 0
#> 39 15.59 1 37 0 1
#> 14 12.89 1 21 0 0
#> 180 14.82 1 37 0 0
#> 86 23.81 1 58 0 1
#> 93 10.33 1 52 0 1
#> 127 3.53 1 62 0 1
#> 70 7.38 1 30 1 0
#> 145 10.07 1 65 1 0
#> 190 20.81 1 42 1 0
#> 23 16.92 1 61 0 0
#> 85 16.44 1 36 0 0
#> 183 9.24 1 67 1 0
#> 63 22.77 1 31 1 0
#> 59 10.16 1 NA 1 0
#> 70.1 7.38 1 30 1 0
#> 164 23.60 1 76 0 1
#> 133 14.65 1 57 0 0
#> 105 19.75 1 60 0 0
#> 175.1 21.91 1 43 0 0
#> 177 12.53 1 75 0 0
#> 5 16.43 1 51 0 1
#> 69 23.23 1 25 0 1
#> 125 15.65 1 67 1 0
#> 113 22.86 1 34 0 0
#> 128 20.35 1 35 0 1
#> 167 15.55 1 56 1 0
#> 155 13.08 1 26 0 0
#> 183.1 9.24 1 67 1 0
#> 43 12.10 1 61 0 1
#> 106 16.67 1 49 1 0
#> 10 10.53 1 34 0 0
#> 171 16.57 1 41 0 1
#> 90 20.94 1 50 0 1
#> 106.1 16.67 1 49 1 0
#> 168 23.72 1 70 0 0
#> 50 10.02 1 NA 1 0
#> 111 17.45 1 47 0 1
#> 128.1 20.35 1 35 0 1
#> 164.1 23.60 1 76 0 1
#> 49 12.19 1 48 1 0
#> 181 16.46 1 45 0 1
#> 18.1 15.21 1 49 1 0
#> 90.1 20.94 1 50 0 1
#> 159 10.55 1 50 0 1
#> 89 11.44 1 NA 0 0
#> 92 22.92 1 47 0 1
#> 89.1 11.44 1 NA 0 0
#> 68 20.62 1 44 0 0
#> 89.2 11.44 1 NA 0 0
#> 197 21.60 1 69 1 0
#> 16.1 8.71 1 71 0 1
#> 13 14.34 1 54 0 1
#> 100 16.07 1 60 0 0
#> 51 18.23 1 83 0 1
#> 99 21.19 1 38 0 1
#> 37 12.52 1 57 1 0
#> 101 9.97 1 10 0 1
#> 175.2 21.91 1 43 0 0
#> 25 6.32 1 34 1 0
#> 18.2 15.21 1 49 1 0
#> 30 17.43 1 78 0 0
#> 195 11.76 1 NA 1 0
#> 81 14.06 1 34 0 0
#> 90.2 20.94 1 50 0 1
#> 56 12.21 1 60 0 0
#> 8 18.43 1 32 0 0
#> 110 17.56 1 65 0 1
#> 166 19.98 1 48 0 0
#> 136.1 21.83 1 43 0 1
#> 175.3 21.91 1 43 0 0
#> 52.1 10.42 1 52 0 1
#> 25.1 6.32 1 34 1 0
#> 125.1 15.65 1 67 1 0
#> 97 19.14 1 65 0 1
#> 155.1 13.08 1 26 0 0
#> 100.1 16.07 1 60 0 0
#> 129.1 23.41 1 53 1 0
#> 78 23.88 1 43 0 0
#> 158 20.14 1 74 1 0
#> 129.2 23.41 1 53 1 0
#> 169 22.41 1 46 0 0
#> 150 20.33 1 48 0 0
#> 195.1 11.76 1 NA 1 0
#> 81.1 14.06 1 34 0 0
#> 157 15.10 1 47 0 0
#> 100.2 16.07 1 60 0 0
#> 149 8.37 1 33 1 0
#> 76 19.22 1 54 0 1
#> 168.1 23.72 1 70 0 0
#> 88.1 18.37 1 47 0 0
#> 136.2 21.83 1 43 0 1
#> 14.1 12.89 1 21 0 0
#> 106.2 16.67 1 49 1 0
#> 125.2 15.65 1 67 1 0
#> 81.2 14.06 1 34 0 0
#> 26 15.77 1 49 0 1
#> 190.1 20.81 1 42 1 0
#> 96 14.54 1 33 0 1
#> 123 13.00 1 44 1 0
#> 26.1 15.77 1 49 0 1
#> 76.1 19.22 1 54 0 1
#> 63.1 22.77 1 31 1 0
#> 3 24.00 0 31 1 0
#> 142 24.00 0 53 0 0
#> 152 24.00 0 36 0 1
#> 48 24.00 0 31 1 0
#> 186 24.00 0 45 1 0
#> 44 24.00 0 56 0 0
#> 196 24.00 0 19 0 0
#> 118 24.00 0 44 1 0
#> 109 24.00 0 48 0 0
#> 115 24.00 0 NA 1 0
#> 87 24.00 0 27 0 0
#> 186.1 24.00 0 45 1 0
#> 28 24.00 0 67 1 0
#> 33 24.00 0 53 0 0
#> 84 24.00 0 39 0 1
#> 198 24.00 0 66 0 1
#> 191 24.00 0 60 0 1
#> 65 24.00 0 57 1 0
#> 112 24.00 0 61 0 0
#> 71 24.00 0 51 0 0
#> 22 24.00 0 52 1 0
#> 172 24.00 0 41 0 0
#> 82 24.00 0 34 0 0
#> 64 24.00 0 43 0 0
#> 121 24.00 0 57 1 0
#> 11 24.00 0 42 0 1
#> 115.1 24.00 0 NA 1 0
#> 44.1 24.00 0 56 0 0
#> 83 24.00 0 6 0 0
#> 2 24.00 0 9 0 0
#> 172.1 24.00 0 41 0 0
#> 191.1 24.00 0 60 0 1
#> 104 24.00 0 50 1 0
#> 64.1 24.00 0 43 0 0
#> 1 24.00 0 23 1 0
#> 193 24.00 0 45 0 1
#> 174 24.00 0 49 1 0
#> 73 24.00 0 NA 0 1
#> 87.1 24.00 0 27 0 0
#> 64.2 24.00 0 43 0 0
#> 94 24.00 0 51 0 1
#> 1.1 24.00 0 23 1 0
#> 22.1 24.00 0 52 1 0
#> 152.1 24.00 0 36 0 1
#> 186.2 24.00 0 45 1 0
#> 20 24.00 0 46 1 0
#> 148 24.00 0 61 1 0
#> 35 24.00 0 51 0 0
#> 163 24.00 0 66 0 0
#> 1.2 24.00 0 23 1 0
#> 186.3 24.00 0 45 1 0
#> 84.1 24.00 0 39 0 1
#> 156 24.00 0 50 1 0
#> 163.1 24.00 0 66 0 0
#> 119 24.00 0 17 0 0
#> 186.4 24.00 0 45 1 0
#> 3.1 24.00 0 31 1 0
#> 193.1 24.00 0 45 0 1
#> 73.1 24.00 0 NA 0 1
#> 54 24.00 0 53 1 0
#> 118.1 24.00 0 44 1 0
#> 132 24.00 0 55 0 0
#> 44.2 24.00 0 56 0 0
#> 65.1 24.00 0 57 1 0
#> 84.2 24.00 0 39 0 1
#> 47 24.00 0 38 0 1
#> 1.3 24.00 0 23 1 0
#> 67 24.00 0 25 0 0
#> 147 24.00 0 76 1 0
#> 152.2 24.00 0 36 0 1
#> 137 24.00 0 45 1 0
#> 1.4 24.00 0 23 1 0
#> 193.2 24.00 0 45 0 1
#> 163.2 24.00 0 66 0 0
#> 178 24.00 0 52 1 0
#> 73.2 24.00 0 NA 0 1
#> 47.1 24.00 0 38 0 1
#> 120 24.00 0 68 0 1
#> 120.1 24.00 0 68 0 1
#> 146 24.00 0 63 1 0
#> 132.1 24.00 0 55 0 0
#> 143 24.00 0 51 0 0
#> 121.1 24.00 0 57 1 0
#> 21 24.00 0 47 0 0
#> 38 24.00 0 31 1 0
#> 35.1 24.00 0 51 0 0
#> 126 24.00 0 48 0 0
#> 122 24.00 0 66 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.688 NA NA NA
#> 2 age, Cure model 0.0171 NA NA NA
#> 3 grade_ii, Cure model -0.196 NA NA NA
#> 4 grade_iii, Cure model 0.598 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00926 NA NA NA
#> 2 grade_ii, Survival model 0.353 NA NA NA
#> 3 grade_iii, Survival model 0.103 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.68816 0.01709 -0.19573 0.59848
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 256.9
#> Residual Deviance: 249.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.68816490 0.01709207 -0.19573155 0.59847826
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.009261564 0.352832931 0.103074151
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.0772007644 0.1029930339 0.5288108722 0.5176341631 0.2724133760
#> [6] 0.8980171669 0.8102521747 0.6074971128 0.0240535778 0.4954340871
#> [11] 0.7009640377 0.5731456148 0.0027156438 0.8350676542 0.9871560625
#> [16] 0.9363353043 0.8476282275 0.1622114232 0.3297017538 0.3895471970
#> [21] 0.8728298136 0.0583964224 0.9363353043 0.0134984337 0.5845215491
#> [26] 0.2277813792 0.0772007644 0.7247051639 0.3998511014 0.0394130809
#> [31] 0.4630785160 0.0518436550 0.1860492952 0.5065155370 0.6654883044
#> [36] 0.8728298136 0.7732626050 0.3397265177 0.7978684274 0.3691665340
#> [41] 0.1393344055 0.3397265177 0.0057949134 0.3100669953 0.1860492952
#> [46] 0.0134984337 0.7610604678 0.3793200037 0.5288108722 0.1393344055
#> [51] 0.7855363880 0.0455079647 0.1779005984 0.1240744281 0.8980171669
#> [56] 0.6190642030 0.4102376567 0.2908791148 0.1316556600 0.7367743897
#> [61] 0.8602299892 0.0772007644 0.9617586434 0.5288108722 0.3198068583
#> [66] 0.6307025592 0.1393344055 0.7488754562 0.2632419837 0.3004128715
#> [71] 0.2191643623 0.1029930339 0.0772007644 0.8102521747 0.9617586434
#> [76] 0.4630785160 0.2541518451 0.6654883044 0.4102376567 0.0240535778
#> [81] 0.0006125142 0.2106672727 0.0240535778 0.0706013981 0.2022660736
#> [86] 0.6307025592 0.5618348205 0.4102376567 0.9235088728 0.2365396729
#> [91] 0.0057949134 0.2724133760 0.1029930339 0.7009640377 0.3397265177
#> [96] 0.4630785160 0.6307025592 0.4416059544 0.1622114232 0.5959890276
#> [101] 0.6890631173 0.4416059544 0.2365396729 0.0583964224 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000
#>
#> $Time
#> 175 136 18 29 88 16 52 57 129 39 14 180 86
#> 21.91 21.83 15.21 15.45 18.37 8.71 10.42 14.46 23.41 15.59 12.89 14.82 23.81
#> 93 127 70 145 190 23 85 183 63 70.1 164 133 105
#> 10.33 3.53 7.38 10.07 20.81 16.92 16.44 9.24 22.77 7.38 23.60 14.65 19.75
#> 175.1 177 5 69 125 113 128 167 155 183.1 43 106 10
#> 21.91 12.53 16.43 23.23 15.65 22.86 20.35 15.55 13.08 9.24 12.10 16.67 10.53
#> 171 90 106.1 168 111 128.1 164.1 49 181 18.1 90.1 159 92
#> 16.57 20.94 16.67 23.72 17.45 20.35 23.60 12.19 16.46 15.21 20.94 10.55 22.92
#> 68 197 16.1 13 100 51 99 37 101 175.2 25 18.2 30
#> 20.62 21.60 8.71 14.34 16.07 18.23 21.19 12.52 9.97 21.91 6.32 15.21 17.43
#> 81 90.2 56 8 110 166 136.1 175.3 52.1 25.1 125.1 97 155.1
#> 14.06 20.94 12.21 18.43 17.56 19.98 21.83 21.91 10.42 6.32 15.65 19.14 13.08
#> 100.1 129.1 78 158 129.2 169 150 81.1 157 100.2 149 76 168.1
#> 16.07 23.41 23.88 20.14 23.41 22.41 20.33 14.06 15.10 16.07 8.37 19.22 23.72
#> 88.1 136.2 14.1 106.2 125.2 81.2 26 190.1 96 123 26.1 76.1 63.1
#> 18.37 21.83 12.89 16.67 15.65 14.06 15.77 20.81 14.54 13.00 15.77 19.22 22.77
#> 3 142 152 48 186 44 196 118 109 87 186.1 28 33
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 84 198 191 65 112 71 22 172 82 64 121 11 44.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 83 2 172.1 191.1 104 64.1 1 193 174 87.1 64.2 94 1.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 22.1 152.1 186.2 20 148 35 163 1.2 186.3 84.1 156 163.1 119
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186.4 3.1 193.1 54 118.1 132 44.2 65.1 84.2 47 1.3 67 147
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152.2 137 1.4 193.2 163.2 178 47.1 120 120.1 146 132.1 143 121.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 21 38 35.1 126 122
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[75]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.003979853 0.183829783 -0.034707325
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.245597868 -0.006829658 -0.324654688
#> grade_iii, Cure model
#> 1.000248642
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 4 17.64 1 NA 0 1
#> 10 10.53 1 34 0 0
#> 63 22.77 1 31 1 0
#> 175 21.91 1 43 0 0
#> 150 20.33 1 48 0 0
#> 90 20.94 1 50 0 1
#> 136 21.83 1 43 0 1
#> 166 19.98 1 48 0 0
#> 114 13.68 1 NA 0 0
#> 117 17.46 1 26 0 1
#> 194 22.40 1 38 0 1
#> 52 10.42 1 52 0 1
#> 139 21.49 1 63 1 0
#> 175.1 21.91 1 43 0 0
#> 129 23.41 1 53 1 0
#> 86 23.81 1 58 0 1
#> 77 7.27 1 67 0 1
#> 60 13.15 1 38 1 0
#> 36 21.19 1 48 0 1
#> 166.1 19.98 1 48 0 0
#> 5 16.43 1 51 0 1
#> 170 19.54 1 43 0 1
#> 70 7.38 1 30 1 0
#> 85 16.44 1 36 0 0
#> 100 16.07 1 60 0 0
#> 36.1 21.19 1 48 0 1
#> 114.1 13.68 1 NA 0 0
#> 136.1 21.83 1 43 0 1
#> 154 12.63 1 20 1 0
#> 111 17.45 1 47 0 1
#> 197 21.60 1 69 1 0
#> 39 15.59 1 37 0 1
#> 42 12.43 1 49 0 1
#> 180 14.82 1 37 0 0
#> 93 10.33 1 52 0 1
#> 42.1 12.43 1 49 0 1
#> 159 10.55 1 50 0 1
#> 86.1 23.81 1 58 0 1
#> 4.1 17.64 1 NA 0 1
#> 55 19.34 1 69 0 1
#> 86.2 23.81 1 58 0 1
#> 8 18.43 1 32 0 0
#> 68 20.62 1 44 0 0
#> 78 23.88 1 43 0 0
#> 45 17.42 1 54 0 1
#> 157 15.10 1 47 0 0
#> 57 14.46 1 45 0 1
#> 159.1 10.55 1 50 0 1
#> 158 20.14 1 74 1 0
#> 175.2 21.91 1 43 0 0
#> 69 23.23 1 25 0 1
#> 157.1 15.10 1 47 0 0
#> 106 16.67 1 49 1 0
#> 16 8.71 1 71 0 1
#> 170.1 19.54 1 43 0 1
#> 26 15.77 1 49 0 1
#> 14 12.89 1 21 0 0
#> 60.1 13.15 1 38 1 0
#> 157.2 15.10 1 47 0 0
#> 99 21.19 1 38 0 1
#> 101 9.97 1 10 0 1
#> 199 19.81 1 NA 0 1
#> 155 13.08 1 26 0 0
#> 85.1 16.44 1 36 0 0
#> 195 11.76 1 NA 1 0
#> 88 18.37 1 47 0 0
#> 175.3 21.91 1 43 0 0
#> 177 12.53 1 75 0 0
#> 184 17.77 1 38 0 0
#> 157.3 15.10 1 47 0 0
#> 136.2 21.83 1 43 0 1
#> 41 18.02 1 40 1 0
#> 189 10.51 1 NA 1 0
#> 49 12.19 1 48 1 0
#> 184.1 17.77 1 38 0 0
#> 149 8.37 1 33 1 0
#> 199.1 19.81 1 NA 0 1
#> 59 10.16 1 NA 1 0
#> 29 15.45 1 68 1 0
#> 113 22.86 1 34 0 0
#> 190 20.81 1 42 1 0
#> 180.1 14.82 1 37 0 0
#> 29.1 15.45 1 68 1 0
#> 190.1 20.81 1 42 1 0
#> 52.1 10.42 1 52 0 1
#> 106.1 16.67 1 49 1 0
#> 130 16.47 1 53 0 1
#> 90.1 20.94 1 50 0 1
#> 130.1 16.47 1 53 0 1
#> 130.2 16.47 1 53 0 1
#> 166.2 19.98 1 48 0 0
#> 157.4 15.10 1 47 0 0
#> 101.1 9.97 1 10 0 1
#> 170.2 19.54 1 43 0 1
#> 40 18.00 1 28 1 0
#> 23 16.92 1 61 0 0
#> 50 10.02 1 NA 1 0
#> 111.1 17.45 1 47 0 1
#> 49.1 12.19 1 48 1 0
#> 70.1 7.38 1 30 1 0
#> 110 17.56 1 65 0 1
#> 69.1 23.23 1 25 0 1
#> 59.1 10.16 1 NA 1 0
#> 32 20.90 1 37 1 0
#> 8.1 18.43 1 32 0 0
#> 111.2 17.45 1 47 0 1
#> 6 15.64 1 39 0 0
#> 50.1 10.02 1 NA 1 0
#> 124 9.73 1 NA 1 0
#> 91 5.33 1 61 0 1
#> 150.1 20.33 1 48 0 0
#> 105 19.75 1 60 0 0
#> 72 24.00 0 40 0 1
#> 95 24.00 0 68 0 1
#> 185 24.00 0 44 1 0
#> 21 24.00 0 47 0 0
#> 200 24.00 0 64 0 0
#> 35 24.00 0 51 0 0
#> 144 24.00 0 28 0 1
#> 104 24.00 0 50 1 0
#> 54 24.00 0 53 1 0
#> 146 24.00 0 63 1 0
#> 19 24.00 0 57 0 1
#> 165 24.00 0 47 0 0
#> 28 24.00 0 67 1 0
#> 156 24.00 0 50 1 0
#> 137 24.00 0 45 1 0
#> 120 24.00 0 68 0 1
#> 102 24.00 0 49 0 0
#> 193 24.00 0 45 0 1
#> 165.1 24.00 0 47 0 0
#> 54.1 24.00 0 53 1 0
#> 103 24.00 0 56 1 0
#> 172 24.00 0 41 0 0
#> 54.2 24.00 0 53 1 0
#> 193.1 24.00 0 45 0 1
#> 98 24.00 0 34 1 0
#> 178 24.00 0 52 1 0
#> 22 24.00 0 52 1 0
#> 173 24.00 0 19 0 1
#> 104.1 24.00 0 50 1 0
#> 103.1 24.00 0 56 1 0
#> 80 24.00 0 41 0 0
#> 146.1 24.00 0 63 1 0
#> 163 24.00 0 66 0 0
#> 163.1 24.00 0 66 0 0
#> 2 24.00 0 9 0 0
#> 62 24.00 0 71 0 0
#> 80.1 24.00 0 41 0 0
#> 33 24.00 0 53 0 0
#> 80.2 24.00 0 41 0 0
#> 146.2 24.00 0 63 1 0
#> 72.1 24.00 0 40 0 1
#> 53 24.00 0 32 0 1
#> 119 24.00 0 17 0 0
#> 165.2 24.00 0 47 0 0
#> 12 24.00 0 63 0 0
#> 84 24.00 0 39 0 1
#> 131 24.00 0 66 0 0
#> 142 24.00 0 53 0 0
#> 12.1 24.00 0 63 0 0
#> 75 24.00 0 21 1 0
#> 64 24.00 0 43 0 0
#> 142.1 24.00 0 53 0 0
#> 75.1 24.00 0 21 1 0
#> 144.1 24.00 0 28 0 1
#> 80.3 24.00 0 41 0 0
#> 116 24.00 0 58 0 1
#> 2.1 24.00 0 9 0 0
#> 27 24.00 0 63 1 0
#> 38 24.00 0 31 1 0
#> 87 24.00 0 27 0 0
#> 137.1 24.00 0 45 1 0
#> 73 24.00 0 NA 0 1
#> 94 24.00 0 51 0 1
#> 80.4 24.00 0 41 0 0
#> 185.1 24.00 0 44 1 0
#> 103.2 24.00 0 56 1 0
#> 163.2 24.00 0 66 0 0
#> 65 24.00 0 57 1 0
#> 152 24.00 0 36 0 1
#> 172.1 24.00 0 41 0 0
#> 156.1 24.00 0 50 1 0
#> 135 24.00 0 58 1 0
#> 19.1 24.00 0 57 0 1
#> 7 24.00 0 37 1 0
#> 73.1 24.00 0 NA 0 1
#> 161 24.00 0 45 0 0
#> 44 24.00 0 56 0 0
#> 102.1 24.00 0 49 0 0
#> 48 24.00 0 31 1 0
#> 22.1 24.00 0 52 1 0
#> 162 24.00 0 51 0 0
#> 156.2 24.00 0 50 1 0
#> 28.1 24.00 0 67 1 0
#> 74 24.00 0 43 0 1
#> 83 24.00 0 6 0 0
#> 156.3 24.00 0 50 1 0
#> 2.2 24.00 0 9 0 0
#> 165.3 24.00 0 47 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.246 NA NA NA
#> 2 age, Cure model -0.00683 NA NA NA
#> 3 grade_ii, Cure model -0.325 NA NA NA
#> 4 grade_iii, Cure model 1.00 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00398 NA NA NA
#> 2 grade_ii, Survival model 0.184 NA NA NA
#> 3 grade_iii, Survival model -0.0347 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.24560 -0.00683 -0.32465 1.00025
#>
#> Degrees of Freedom: 184 Total (i.e. Null); 181 Residual
#> Null Deviance: 255.6
#> Residual Deviance: 242.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.245597868 -0.006829658 -0.324654688 1.000248642
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.003979853 0.183829783 -0.034707325
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.861426592 0.061521211 0.078526004 0.235901186 0.179677953 0.109585506
#> [7] 0.264570960 0.424328909 0.069935390 0.872897097 0.143957799 0.078526004
#> [13] 0.029578680 0.011388205 0.976702624 0.725874831 0.153070437 0.264570960
#> [19] 0.561252881 0.303087428 0.953648062 0.539772914 0.572142153 0.153070437
#> [25] 0.109585506 0.770830809 0.434747127 0.134882515 0.605056323 0.793436405
#> [31] 0.692268489 0.895815862 0.793436405 0.838676405 0.011388205 0.332427539
#> [37] 0.011388205 0.342592344 0.226356537 0.003476162 0.465691454 0.638038525
#> [43] 0.714590884 0.838676405 0.254866440 0.078526004 0.037712349 0.638038525
#> [49] 0.486952924 0.930407146 0.303087428 0.583075633 0.759530924 0.725874831
#> [55] 0.638038525 0.153070437 0.907381461 0.748244504 0.539772914 0.362761657
#> [61] 0.078526004 0.782112530 0.393561956 0.638038525 0.109585506 0.373039985
#> [67] 0.816054135 0.393561956 0.942031466 0.616094693 0.053036668 0.207792831
#> [73] 0.692268489 0.616094693 0.207792831 0.872897097 0.486952924 0.508042641
#> [79] 0.179677953 0.508042641 0.508042641 0.264570960 0.638038525 0.907381461
#> [85] 0.303087428 0.383311273 0.476296613 0.434747127 0.816054135 0.953648062
#> [91] 0.413943610 0.037712349 0.198279819 0.342592344 0.434747127 0.594051360
#> [97] 0.988334678 0.235901186 0.293159317 0.000000000 0.000000000 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 10 63 175 150 90 136 166 117 194 52 139 175.1 129
#> 10.53 22.77 21.91 20.33 20.94 21.83 19.98 17.46 22.40 10.42 21.49 21.91 23.41
#> 86 77 60 36 166.1 5 170 70 85 100 36.1 136.1 154
#> 23.81 7.27 13.15 21.19 19.98 16.43 19.54 7.38 16.44 16.07 21.19 21.83 12.63
#> 111 197 39 42 180 93 42.1 159 86.1 55 86.2 8 68
#> 17.45 21.60 15.59 12.43 14.82 10.33 12.43 10.55 23.81 19.34 23.81 18.43 20.62
#> 78 45 157 57 159.1 158 175.2 69 157.1 106 16 170.1 26
#> 23.88 17.42 15.10 14.46 10.55 20.14 21.91 23.23 15.10 16.67 8.71 19.54 15.77
#> 14 60.1 157.2 99 101 155 85.1 88 175.3 177 184 157.3 136.2
#> 12.89 13.15 15.10 21.19 9.97 13.08 16.44 18.37 21.91 12.53 17.77 15.10 21.83
#> 41 49 184.1 149 29 113 190 180.1 29.1 190.1 52.1 106.1 130
#> 18.02 12.19 17.77 8.37 15.45 22.86 20.81 14.82 15.45 20.81 10.42 16.67 16.47
#> 90.1 130.1 130.2 166.2 157.4 101.1 170.2 40 23 111.1 49.1 70.1 110
#> 20.94 16.47 16.47 19.98 15.10 9.97 19.54 18.00 16.92 17.45 12.19 7.38 17.56
#> 69.1 32 8.1 111.2 6 91 150.1 105 72 95 185 21 200
#> 23.23 20.90 18.43 17.45 15.64 5.33 20.33 19.75 24.00 24.00 24.00 24.00 24.00
#> 35 144 104 54 146 19 165 28 156 137 120 102 193
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165.1 54.1 103 172 54.2 193.1 98 178 22 173 104.1 103.1 80
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 146.1 163 163.1 2 62 80.1 33 80.2 146.2 72.1 53 119 165.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12 84 131 142 12.1 75 64 142.1 75.1 144.1 80.3 116 2.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 27 38 87 137.1 94 80.4 185.1 103.2 163.2 65 152 172.1 156.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135 19.1 7 161 44 102.1 48 22.1 162 156.2 28.1 74 83
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156.3 2.2 165.3
#> 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[76]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.009733158 0.269964016 0.087720067
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.18940193 0.03094427 -0.70635092
#> grade_iii, Cure model
#> 0.88913897
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 155 13.08 1 26 0 0
#> 78 23.88 1 43 0 0
#> 194 22.40 1 38 0 1
#> 106 16.67 1 49 1 0
#> 177 12.53 1 75 0 0
#> 57 14.46 1 45 0 1
#> 175 21.91 1 43 0 0
#> 197 21.60 1 69 1 0
#> 5 16.43 1 51 0 1
#> 92 22.92 1 47 0 1
#> 177.1 12.53 1 75 0 0
#> 49 12.19 1 48 1 0
#> 168 23.72 1 70 0 0
#> 170 19.54 1 43 0 1
#> 56 12.21 1 60 0 0
#> 111 17.45 1 47 0 1
#> 117 17.46 1 26 0 1
#> 133 14.65 1 57 0 0
#> 153 21.33 1 55 1 0
#> 157 15.10 1 47 0 0
#> 86 23.81 1 58 0 1
#> 63 22.77 1 31 1 0
#> 13 14.34 1 54 0 1
#> 81 14.06 1 34 0 0
#> 195 11.76 1 NA 1 0
#> 190 20.81 1 42 1 0
#> 100 16.07 1 60 0 0
#> 195.1 11.76 1 NA 1 0
#> 177.2 12.53 1 75 0 0
#> 25 6.32 1 34 1 0
#> 107 11.18 1 54 1 0
#> 91 5.33 1 61 0 1
#> 187 9.92 1 39 1 0
#> 14 12.89 1 21 0 0
#> 92.1 22.92 1 47 0 1
#> 111.1 17.45 1 47 0 1
#> 108 18.29 1 39 0 1
#> 101 9.97 1 10 0 1
#> 179 18.63 1 42 0 0
#> 45 17.42 1 54 0 1
#> 68 20.62 1 44 0 0
#> 15 22.68 1 48 0 0
#> 129 23.41 1 53 1 0
#> 42 12.43 1 49 0 1
#> 145 10.07 1 65 1 0
#> 37 12.52 1 57 1 0
#> 181 16.46 1 45 0 1
#> 168.1 23.72 1 70 0 0
#> 30 17.43 1 78 0 0
#> 195.2 11.76 1 NA 1 0
#> 63.1 22.77 1 31 1 0
#> 189 10.51 1 NA 1 0
#> 177.3 12.53 1 75 0 0
#> 52 10.42 1 52 0 1
#> 40 18.00 1 28 1 0
#> 37.1 12.52 1 57 1 0
#> 180 14.82 1 37 0 0
#> 29 15.45 1 68 1 0
#> 90 20.94 1 50 0 1
#> 127 3.53 1 62 0 1
#> 164 23.60 1 76 0 1
#> 8 18.43 1 32 0 0
#> 157.1 15.10 1 47 0 0
#> 164.1 23.60 1 76 0 1
#> 50 10.02 1 NA 1 0
#> 167 15.55 1 56 1 0
#> 145.1 10.07 1 65 1 0
#> 29.1 15.45 1 68 1 0
#> 78.1 23.88 1 43 0 0
#> 187.1 9.92 1 39 1 0
#> 61 10.12 1 36 0 1
#> 76 19.22 1 54 0 1
#> 169 22.41 1 46 0 0
#> 5.1 16.43 1 51 0 1
#> 91.1 5.33 1 61 0 1
#> 190.1 20.81 1 42 1 0
#> 70 7.38 1 30 1 0
#> 42.1 12.43 1 49 0 1
#> 10 10.53 1 34 0 0
#> 166 19.98 1 48 0 0
#> 91.2 5.33 1 61 0 1
#> 127.1 3.53 1 62 0 1
#> 130 16.47 1 53 0 1
#> 125 15.65 1 67 1 0
#> 13.1 14.34 1 54 0 1
#> 37.2 12.52 1 57 1 0
#> 170.1 19.54 1 43 0 1
#> 181.1 16.46 1 45 0 1
#> 129.1 23.41 1 53 1 0
#> 51 18.23 1 83 0 1
#> 155.1 13.08 1 26 0 0
#> 56.1 12.21 1 60 0 0
#> 110 17.56 1 65 0 1
#> 197.1 21.60 1 69 1 0
#> 155.2 13.08 1 26 0 0
#> 124 9.73 1 NA 1 0
#> 169.1 22.41 1 46 0 0
#> 136 21.83 1 43 0 1
#> 123 13.00 1 44 1 0
#> 130.1 16.47 1 53 0 1
#> 164.2 23.60 1 76 0 1
#> 69 23.23 1 25 0 1
#> 164.3 23.60 1 76 0 1
#> 111.2 17.45 1 47 0 1
#> 139 21.49 1 63 1 0
#> 105 19.75 1 60 0 0
#> 157.2 15.10 1 47 0 0
#> 10.1 10.53 1 34 0 0
#> 155.3 13.08 1 26 0 0
#> 45.1 17.42 1 54 0 1
#> 197.2 21.60 1 69 1 0
#> 179.1 18.63 1 42 0 0
#> 84 24.00 0 39 0 1
#> 132 24.00 0 55 0 0
#> 21 24.00 0 47 0 0
#> 146 24.00 0 63 1 0
#> 17 24.00 0 38 0 1
#> 109 24.00 0 48 0 0
#> 176 24.00 0 43 0 1
#> 119 24.00 0 17 0 0
#> 147 24.00 0 76 1 0
#> 137 24.00 0 45 1 0
#> 141 24.00 0 44 1 0
#> 137.1 24.00 0 45 1 0
#> 132.1 24.00 0 55 0 0
#> 156 24.00 0 50 1 0
#> 103 24.00 0 56 1 0
#> 115 24.00 0 NA 1 0
#> 182 24.00 0 35 0 0
#> 141.1 24.00 0 44 1 0
#> 185 24.00 0 44 1 0
#> 104 24.00 0 50 1 0
#> 82 24.00 0 34 0 0
#> 73 24.00 0 NA 0 1
#> 182.1 24.00 0 35 0 0
#> 146.1 24.00 0 63 1 0
#> 54 24.00 0 53 1 0
#> 182.2 24.00 0 35 0 0
#> 46 24.00 0 71 0 0
#> 173 24.00 0 19 0 1
#> 72 24.00 0 40 0 1
#> 27 24.00 0 63 1 0
#> 104.1 24.00 0 50 1 0
#> 135 24.00 0 58 1 0
#> 1 24.00 0 23 1 0
#> 103.1 24.00 0 56 1 0
#> 67 24.00 0 25 0 0
#> 87 24.00 0 27 0 0
#> 3 24.00 0 31 1 0
#> 162 24.00 0 51 0 0
#> 147.1 24.00 0 76 1 0
#> 135.1 24.00 0 58 1 0
#> 22 24.00 0 52 1 0
#> 165 24.00 0 47 0 0
#> 38 24.00 0 31 1 0
#> 119.1 24.00 0 17 0 0
#> 73.1 24.00 0 NA 0 1
#> 141.2 24.00 0 44 1 0
#> 182.3 24.00 0 35 0 0
#> 72.1 24.00 0 40 0 1
#> 9 24.00 0 31 1 0
#> 156.1 24.00 0 50 1 0
#> 7 24.00 0 37 1 0
#> 143 24.00 0 51 0 0
#> 137.2 24.00 0 45 1 0
#> 27.1 24.00 0 63 1 0
#> 148 24.00 0 61 1 0
#> 173.1 24.00 0 19 0 1
#> 163 24.00 0 66 0 0
#> 80 24.00 0 41 0 0
#> 94 24.00 0 51 0 1
#> 31 24.00 0 36 0 1
#> 75 24.00 0 21 1 0
#> 172 24.00 0 41 0 0
#> 2 24.00 0 9 0 0
#> 151 24.00 0 42 0 0
#> 186 24.00 0 45 1 0
#> 48 24.00 0 31 1 0
#> 75.1 24.00 0 21 1 0
#> 95 24.00 0 68 0 1
#> 115.1 24.00 0 NA 1 0
#> 84.1 24.00 0 39 0 1
#> 131 24.00 0 66 0 0
#> 27.2 24.00 0 63 1 0
#> 132.2 24.00 0 55 0 0
#> 200 24.00 0 64 0 0
#> 151.1 24.00 0 42 0 0
#> 65 24.00 0 57 1 0
#> 178 24.00 0 52 1 0
#> 22.1 24.00 0 52 1 0
#> 73.2 24.00 0 NA 0 1
#> 95.1 24.00 0 68 0 1
#> 98 24.00 0 34 1 0
#> 11 24.00 0 42 0 1
#> 2.1 24.00 0 9 0 0
#> 67.1 24.00 0 25 0 0
#> 103.2 24.00 0 56 1 0
#> 1.1 24.00 0 23 1 0
#> 82.1 24.00 0 34 0 0
#> 174 24.00 0 49 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.19 NA NA NA
#> 2 age, Cure model 0.0309 NA NA NA
#> 3 grade_ii, Cure model -0.706 NA NA NA
#> 4 grade_iii, Cure model 0.889 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00973 NA NA NA
#> 2 grade_ii, Survival model 0.270 NA NA NA
#> 3 grade_iii, Survival model 0.0877 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.18940 0.03094 -0.70635 0.88914
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 259.2
#> Residual Deviance: 234.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.18940193 0.03094427 -0.70635092 0.88913897
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.009733158 0.269964016 0.087720067
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.5614445894 0.0008500588 0.0849080474 0.3384931830 0.6304199884
#> [6] 0.5160000819 0.0914711391 0.1050603315 0.3880958956 0.0439923768
#> [11] 0.6304199884 0.7645121340 0.0065116062 0.1869246072 0.7393210762
#> [16] 0.2823121069 0.2731591820 0.5047950473 0.1329547913 0.4613526450
#> [21] 0.0038855704 0.0551691052 0.5272774894 0.5499311322 0.1480300257
#> [26] 0.4085027263 0.6304199884 0.9201880541 0.7772510515 0.9333816256
#> [31] 0.8808407084 0.6186449033 0.0439923768 0.2823121069 0.2372904435
#> [36] 0.8677004705 0.2116083387 0.3192510717 0.1630437077 0.0664248479
#> [41] 0.0284075227 0.7145040959 0.8416227435 0.6780089017 0.3680429479
#> [46] 0.0065116062 0.3096882192 0.0551691052 0.6304199884 0.8156342887
#> [51] 0.2550764559 0.6780089017 0.4936949338 0.4400854510 0.1404258317
#> [56] 0.9730644708 0.0128308533 0.2285619817 0.4613526450 0.0128308533
#> [61] 0.4294883697 0.8416227435 0.4400854510 0.0008500588 0.8808407084
#> [66] 0.8286049777 0.2031860516 0.0725155291 0.3880958956 0.9333816256
#> [71] 0.1480300257 0.9070056640 0.7145040959 0.7900372433 0.1708602519
#> [76] 0.9333816256 0.9730644708 0.3483079307 0.4189538103 0.5272774894
#> [81] 0.6780089017 0.1869246072 0.3680429479 0.0284075227 0.2461009708
#> [86] 0.5614445894 0.7393210762 0.2640527824 0.1050603315 0.5614445894
#> [91] 0.0725155291 0.0981994668 0.6069111100 0.3483079307 0.0128308533
#> [96] 0.0384683250 0.0128308533 0.2823121069 0.1255804139 0.1788126237
#> [101] 0.4613526450 0.7900372433 0.5614445894 0.3192510717 0.1050603315
#> [106] 0.2116083387 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#>
#> $Time
#> 155 78 194 106 177 57 175 197 5 92 177.1 49 168
#> 13.08 23.88 22.40 16.67 12.53 14.46 21.91 21.60 16.43 22.92 12.53 12.19 23.72
#> 170 56 111 117 133 153 157 86 63 13 81 190 100
#> 19.54 12.21 17.45 17.46 14.65 21.33 15.10 23.81 22.77 14.34 14.06 20.81 16.07
#> 177.2 25 107 91 187 14 92.1 111.1 108 101 179 45 68
#> 12.53 6.32 11.18 5.33 9.92 12.89 22.92 17.45 18.29 9.97 18.63 17.42 20.62
#> 15 129 42 145 37 181 168.1 30 63.1 177.3 52 40 37.1
#> 22.68 23.41 12.43 10.07 12.52 16.46 23.72 17.43 22.77 12.53 10.42 18.00 12.52
#> 180 29 90 127 164 8 157.1 164.1 167 145.1 29.1 78.1 187.1
#> 14.82 15.45 20.94 3.53 23.60 18.43 15.10 23.60 15.55 10.07 15.45 23.88 9.92
#> 61 76 169 5.1 91.1 190.1 70 42.1 10 166 91.2 127.1 130
#> 10.12 19.22 22.41 16.43 5.33 20.81 7.38 12.43 10.53 19.98 5.33 3.53 16.47
#> 125 13.1 37.2 170.1 181.1 129.1 51 155.1 56.1 110 197.1 155.2 169.1
#> 15.65 14.34 12.52 19.54 16.46 23.41 18.23 13.08 12.21 17.56 21.60 13.08 22.41
#> 136 123 130.1 164.2 69 164.3 111.2 139 105 157.2 10.1 155.3 45.1
#> 21.83 13.00 16.47 23.60 23.23 23.60 17.45 21.49 19.75 15.10 10.53 13.08 17.42
#> 197.2 179.1 84 132 21 146 17 109 176 119 147 137 141
#> 21.60 18.63 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137.1 132.1 156 103 182 141.1 185 104 82 182.1 146.1 54 182.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 46 173 72 27 104.1 135 1 103.1 67 87 3 162 147.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135.1 22 165 38 119.1 141.2 182.3 72.1 9 156.1 7 143 137.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 27.1 148 173.1 163 80 94 31 75 172 2 151 186 48
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75.1 95 84.1 131 27.2 132.2 200 151.1 65 178 22.1 95.1 98
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 11 2.1 67.1 103.2 1.1 82.1 174
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[77]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.00262855 0.37607073 0.36318387
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.321177458 0.007984163 -0.178181850
#> grade_iii, Cure model
#> 0.744744321
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 124 9.73 1 NA 1 0
#> 100 16.07 1 60 0 0
#> 117 17.46 1 26 0 1
#> 99 21.19 1 38 0 1
#> 192 16.44 1 31 1 0
#> 45 17.42 1 54 0 1
#> 125 15.65 1 67 1 0
#> 166 19.98 1 48 0 0
#> 117.1 17.46 1 26 0 1
#> 16 8.71 1 71 0 1
#> 36 21.19 1 48 0 1
#> 6 15.64 1 39 0 0
#> 179 18.63 1 42 0 0
#> 5 16.43 1 51 0 1
#> 92 22.92 1 47 0 1
#> 63 22.77 1 31 1 0
#> 55 19.34 1 69 0 1
#> 30 17.43 1 78 0 0
#> 68 20.62 1 44 0 0
#> 18 15.21 1 49 1 0
#> 190 20.81 1 42 1 0
#> 100.1 16.07 1 60 0 0
#> 93 10.33 1 52 0 1
#> 25 6.32 1 34 1 0
#> 101 9.97 1 10 0 1
#> 108 18.29 1 39 0 1
#> 97 19.14 1 65 0 1
#> 100.2 16.07 1 60 0 0
#> 140 12.68 1 59 1 0
#> 97.1 19.14 1 65 0 1
#> 157 15.10 1 47 0 0
#> 85 16.44 1 36 0 0
#> 76 19.22 1 54 0 1
#> 51 18.23 1 83 0 1
#> 63.1 22.77 1 31 1 0
#> 183 9.24 1 67 1 0
#> 127 3.53 1 62 0 1
#> 169 22.41 1 46 0 0
#> 23 16.92 1 61 0 0
#> 58 19.34 1 39 0 0
#> 124.1 9.73 1 NA 1 0
#> 50 10.02 1 NA 1 0
#> 189 10.51 1 NA 1 0
#> 170 19.54 1 43 0 1
#> 91 5.33 1 61 0 1
#> 85.1 16.44 1 36 0 0
#> 70 7.38 1 30 1 0
#> 114 13.68 1 NA 0 0
#> 133 14.65 1 57 0 0
#> 43 12.10 1 61 0 1
#> 6.1 15.64 1 39 0 0
#> 50.1 10.02 1 NA 1 0
#> 114.1 13.68 1 NA 0 0
#> 111 17.45 1 47 0 1
#> 100.3 16.07 1 60 0 0
#> 42 12.43 1 49 0 1
#> 107 11.18 1 54 1 0
#> 114.2 13.68 1 NA 0 0
#> 15 22.68 1 48 0 0
#> 164 23.60 1 76 0 1
#> 164.1 23.60 1 76 0 1
#> 79 16.23 1 54 1 0
#> 106 16.67 1 49 1 0
#> 10 10.53 1 34 0 0
#> 68.1 20.62 1 44 0 0
#> 61 10.12 1 36 0 1
#> 171 16.57 1 41 0 1
#> 190.1 20.81 1 42 1 0
#> 127.1 3.53 1 62 0 1
#> 190.2 20.81 1 42 1 0
#> 113 22.86 1 34 0 0
#> 70.1 7.38 1 30 1 0
#> 68.2 20.62 1 44 0 0
#> 24 23.89 1 38 0 0
#> 154 12.63 1 20 1 0
#> 106.1 16.67 1 49 1 0
#> 106.2 16.67 1 49 1 0
#> 113.1 22.86 1 34 0 0
#> 14 12.89 1 21 0 0
#> 36.1 21.19 1 48 0 1
#> 159 10.55 1 50 0 1
#> 179.1 18.63 1 42 0 0
#> 32 20.90 1 37 1 0
#> 134 17.81 1 47 1 0
#> 158 20.14 1 74 1 0
#> 68.3 20.62 1 44 0 0
#> 37 12.52 1 57 1 0
#> 99.1 21.19 1 38 0 1
#> 190.3 20.81 1 42 1 0
#> 179.2 18.63 1 42 0 0
#> 41 18.02 1 40 1 0
#> 129 23.41 1 53 1 0
#> 8 18.43 1 32 0 0
#> 168 23.72 1 70 0 0
#> 139 21.49 1 63 1 0
#> 194 22.40 1 38 0 1
#> 149 8.37 1 33 1 0
#> 177 12.53 1 75 0 0
#> 18.1 15.21 1 49 1 0
#> 26 15.77 1 49 0 1
#> 56 12.21 1 60 0 0
#> 14.1 12.89 1 21 0 0
#> 26.1 15.77 1 49 0 1
#> 169.1 22.41 1 46 0 0
#> 169.2 22.41 1 46 0 0
#> 111.1 17.45 1 47 0 1
#> 184 17.77 1 38 0 0
#> 78 23.88 1 43 0 0
#> 171.1 16.57 1 41 0 1
#> 91.1 5.33 1 61 0 1
#> 5.1 16.43 1 51 0 1
#> 110 17.56 1 65 0 1
#> 33 24.00 0 53 0 0
#> 151 24.00 0 42 0 0
#> 98 24.00 0 34 1 0
#> 98.1 24.00 0 34 1 0
#> 94 24.00 0 51 0 1
#> 135 24.00 0 58 1 0
#> 67 24.00 0 25 0 0
#> 163 24.00 0 66 0 0
#> 161 24.00 0 45 0 0
#> 161.1 24.00 0 45 0 0
#> 44 24.00 0 56 0 0
#> 118 24.00 0 44 1 0
#> 115 24.00 0 NA 1 0
#> 141 24.00 0 44 1 0
#> 193 24.00 0 45 0 1
#> 147 24.00 0 76 1 0
#> 144 24.00 0 28 0 1
#> 146 24.00 0 63 1 0
#> 196 24.00 0 19 0 0
#> 115.1 24.00 0 NA 1 0
#> 120 24.00 0 68 0 1
#> 71 24.00 0 51 0 0
#> 65 24.00 0 57 1 0
#> 196.1 24.00 0 19 0 0
#> 185 24.00 0 44 1 0
#> 62 24.00 0 71 0 0
#> 20 24.00 0 46 1 0
#> 62.1 24.00 0 71 0 0
#> 165 24.00 0 47 0 0
#> 152 24.00 0 36 0 1
#> 165.1 24.00 0 47 0 0
#> 193.1 24.00 0 45 0 1
#> 160 24.00 0 31 1 0
#> 98.2 24.00 0 34 1 0
#> 146.1 24.00 0 63 1 0
#> 115.2 24.00 0 NA 1 0
#> 112 24.00 0 61 0 0
#> 131 24.00 0 66 0 0
#> 98.3 24.00 0 34 1 0
#> 152.1 24.00 0 36 0 1
#> 178 24.00 0 52 1 0
#> 38 24.00 0 31 1 0
#> 182 24.00 0 35 0 0
#> 186 24.00 0 45 1 0
#> 182.1 24.00 0 35 0 0
#> 11 24.00 0 42 0 1
#> 165.2 24.00 0 47 0 0
#> 72 24.00 0 40 0 1
#> 172 24.00 0 41 0 0
#> 102 24.00 0 49 0 0
#> 163.1 24.00 0 66 0 0
#> 165.3 24.00 0 47 0 0
#> 71.1 24.00 0 51 0 0
#> 173 24.00 0 19 0 1
#> 118.1 24.00 0 44 1 0
#> 142 24.00 0 53 0 0
#> 141.1 24.00 0 44 1 0
#> 98.4 24.00 0 34 1 0
#> 156 24.00 0 50 1 0
#> 3 24.00 0 31 1 0
#> 102.1 24.00 0 49 0 0
#> 22 24.00 0 52 1 0
#> 46 24.00 0 71 0 0
#> 173.1 24.00 0 19 0 1
#> 7 24.00 0 37 1 0
#> 35 24.00 0 51 0 0
#> 74 24.00 0 43 0 1
#> 3.1 24.00 0 31 1 0
#> 151.1 24.00 0 42 0 0
#> 152.2 24.00 0 36 0 1
#> 147.1 24.00 0 76 1 0
#> 82 24.00 0 34 0 0
#> 17 24.00 0 38 0 1
#> 103 24.00 0 56 1 0
#> 131.1 24.00 0 66 0 0
#> 178.1 24.00 0 52 1 0
#> 35.1 24.00 0 51 0 0
#> 31 24.00 0 36 0 1
#> 146.2 24.00 0 63 1 0
#> 103.1 24.00 0 56 1 0
#> 156.1 24.00 0 50 1 0
#> 198 24.00 0 66 0 1
#> 172.1 24.00 0 41 0 0
#> 3.2 24.00 0 31 1 0
#> 156.2 24.00 0 50 1 0
#> 87 24.00 0 27 0 0
#> 193.2 24.00 0 45 0 1
#> 71.2 24.00 0 51 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.321 NA NA NA
#> 2 age, Cure model 0.00798 NA NA NA
#> 3 grade_ii, Cure model -0.178 NA NA NA
#> 4 grade_iii, Cure model 0.745 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00263 NA NA NA
#> 2 grade_ii, Survival model 0.376 NA NA NA
#> 3 grade_iii, Survival model 0.363 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.321177 0.007984 -0.178182 0.744744
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.1
#> Residual Deviance: 252.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.321177458 0.007984163 -0.178181850 0.744744321
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.00262855 0.37607073 0.36318387
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.669129088 0.506779053 0.209720862 0.615932017 0.552732574 0.721920023
#> [7] 0.344356299 0.506779053 0.923671108 0.209720862 0.730784665 0.411861038
#> [13] 0.642517905 0.085488466 0.120924410 0.363993324 0.543490898 0.296723259
#> [19] 0.748447936 0.259438610 0.669129088 0.889031221 0.957837983 0.906406255
#> [25] 0.449792323 0.392924031 0.669129088 0.801303412 0.392924031 0.765995062
#> [31] 0.615932017 0.383238490 0.459383703 0.120924410 0.915047694 0.983201747
#> [37] 0.154273335 0.561936150 0.363993324 0.354213477 0.966339642 0.615932017
#> [43] 0.940860315 0.774831286 0.854095739 0.730784665 0.525221791 0.669129088
#> [49] 0.836546581 0.862856709 0.142781880 0.048775984 0.048775984 0.660239636
#> [55] 0.571162115 0.880309057 0.296723259 0.897731688 0.598036185 0.259438610
#> [61] 0.983201747 0.259438610 0.097641978 0.940860315 0.296723259 0.006333254
#> [67] 0.810139163 0.571162115 0.571162115 0.097641978 0.783681554 0.209720862
#> [73] 0.871594275 0.411861038 0.249091984 0.478443920 0.334532469 0.296723259
#> [79] 0.827754307 0.209720862 0.259438610 0.411861038 0.468943941 0.072852542
#> [85] 0.440139657 0.033348426 0.198455847 0.187039239 0.932279003 0.818938261
#> [91] 0.748447936 0.704251868 0.845314515 0.783681554 0.704251868 0.154273335
#> [97] 0.154273335 0.525221791 0.487890025 0.019122352 0.598036185 0.966339642
#> [103] 0.642517905 0.497353552 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 100 117 99 192 45 125 166 117.1 16 36 6 179 5
#> 16.07 17.46 21.19 16.44 17.42 15.65 19.98 17.46 8.71 21.19 15.64 18.63 16.43
#> 92 63 55 30 68 18 190 100.1 93 25 101 108 97
#> 22.92 22.77 19.34 17.43 20.62 15.21 20.81 16.07 10.33 6.32 9.97 18.29 19.14
#> 100.2 140 97.1 157 85 76 51 63.1 183 127 169 23 58
#> 16.07 12.68 19.14 15.10 16.44 19.22 18.23 22.77 9.24 3.53 22.41 16.92 19.34
#> 170 91 85.1 70 133 43 6.1 111 100.3 42 107 15 164
#> 19.54 5.33 16.44 7.38 14.65 12.10 15.64 17.45 16.07 12.43 11.18 22.68 23.60
#> 164.1 79 106 10 68.1 61 171 190.1 127.1 190.2 113 70.1 68.2
#> 23.60 16.23 16.67 10.53 20.62 10.12 16.57 20.81 3.53 20.81 22.86 7.38 20.62
#> 24 154 106.1 106.2 113.1 14 36.1 159 179.1 32 134 158 68.3
#> 23.89 12.63 16.67 16.67 22.86 12.89 21.19 10.55 18.63 20.90 17.81 20.14 20.62
#> 37 99.1 190.3 179.2 41 129 8 168 139 194 149 177 18.1
#> 12.52 21.19 20.81 18.63 18.02 23.41 18.43 23.72 21.49 22.40 8.37 12.53 15.21
#> 26 56 14.1 26.1 169.1 169.2 111.1 184 78 171.1 91.1 5.1 110
#> 15.77 12.21 12.89 15.77 22.41 22.41 17.45 17.77 23.88 16.57 5.33 16.43 17.56
#> 33 151 98 98.1 94 135 67 163 161 161.1 44 118 141
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193 147 144 146 196 120 71 65 196.1 185 62 20 62.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165 152 165.1 193.1 160 98.2 146.1 112 131 98.3 152.1 178 38
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 182 186 182.1 11 165.2 72 172 102 163.1 165.3 71.1 173 118.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142 141.1 98.4 156 3 102.1 22 46 173.1 7 35 74 3.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 151.1 152.2 147.1 82 17 103 131.1 178.1 35.1 31 146.2 103.1 156.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 198 172.1 3.2 156.2 87 193.2 71.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[78]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.003421334 0.738087033 0.692344232
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.707014664 0.009328147 0.226675791
#> grade_iii, Cure model
#> 1.119351472
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 79 16.23 1 54 1 0
#> 111 17.45 1 47 0 1
#> 16 8.71 1 71 0 1
#> 128 20.35 1 35 0 1
#> 92 22.92 1 47 0 1
#> 99 21.19 1 38 0 1
#> 96 14.54 1 33 0 1
#> 10 10.53 1 34 0 0
#> 101 9.97 1 10 0 1
#> 32 20.90 1 37 1 0
#> 114 13.68 1 NA 0 0
#> 100 16.07 1 60 0 0
#> 70 7.38 1 30 1 0
#> 197 21.60 1 69 1 0
#> 5 16.43 1 51 0 1
#> 155 13.08 1 26 0 0
#> 114.1 13.68 1 NA 0 0
#> 101.1 9.97 1 10 0 1
#> 92.1 22.92 1 47 0 1
#> 63 22.77 1 31 1 0
#> 113 22.86 1 34 0 0
#> 175 21.91 1 43 0 0
#> 78 23.88 1 43 0 0
#> 125 15.65 1 67 1 0
#> 4 17.64 1 NA 0 1
#> 140 12.68 1 59 1 0
#> 195 11.76 1 NA 1 0
#> 129 23.41 1 53 1 0
#> 66 22.13 1 53 0 0
#> 16.1 8.71 1 71 0 1
#> 101.2 9.97 1 10 0 1
#> 43 12.10 1 61 0 1
#> 169 22.41 1 46 0 0
#> 63.1 22.77 1 31 1 0
#> 136 21.83 1 43 0 1
#> 89 11.44 1 NA 0 0
#> 60 13.15 1 38 1 0
#> 5.1 16.43 1 51 0 1
#> 130 16.47 1 53 0 1
#> 16.2 8.71 1 71 0 1
#> 136.1 21.83 1 43 0 1
#> 197.1 21.60 1 69 1 0
#> 128.1 20.35 1 35 0 1
#> 114.2 13.68 1 NA 0 0
#> 107 11.18 1 54 1 0
#> 88 18.37 1 47 0 0
#> 45 17.42 1 54 0 1
#> 41 18.02 1 40 1 0
#> 24 23.89 1 38 0 0
#> 78.1 23.88 1 43 0 0
#> 117 17.46 1 26 0 1
#> 51 18.23 1 83 0 1
#> 5.2 16.43 1 51 0 1
#> 192 16.44 1 31 1 0
#> 124 9.73 1 NA 1 0
#> 145 10.07 1 65 1 0
#> 10.1 10.53 1 34 0 0
#> 97 19.14 1 65 0 1
#> 183 9.24 1 67 1 0
#> 8 18.43 1 32 0 0
#> 58 19.34 1 39 0 0
#> 43.1 12.10 1 61 0 1
#> 89.1 11.44 1 NA 0 0
#> 190 20.81 1 42 1 0
#> 16.3 8.71 1 71 0 1
#> 43.2 12.10 1 61 0 1
#> 50 10.02 1 NA 1 0
#> 170 19.54 1 43 0 1
#> 77 7.27 1 67 0 1
#> 170.1 19.54 1 43 0 1
#> 111.1 17.45 1 47 0 1
#> 145.1 10.07 1 65 1 0
#> 61 10.12 1 36 0 1
#> 14 12.89 1 21 0 0
#> 139 21.49 1 63 1 0
#> 145.2 10.07 1 65 1 0
#> 69 23.23 1 25 0 1
#> 23 16.92 1 61 0 0
#> 96.1 14.54 1 33 0 1
#> 79.1 16.23 1 54 1 0
#> 99.1 21.19 1 38 0 1
#> 140.1 12.68 1 59 1 0
#> 14.1 12.89 1 21 0 0
#> 39 15.59 1 37 0 1
#> 187 9.92 1 39 1 0
#> 125.1 15.65 1 67 1 0
#> 155.1 13.08 1 26 0 0
#> 197.2 21.60 1 69 1 0
#> 18 15.21 1 49 1 0
#> 81 14.06 1 34 0 0
#> 113.1 22.86 1 34 0 0
#> 90 20.94 1 50 0 1
#> 86 23.81 1 58 0 1
#> 100.1 16.07 1 60 0 0
#> 128.2 20.35 1 35 0 1
#> 92.2 22.92 1 47 0 1
#> 127 3.53 1 62 0 1
#> 105 19.75 1 60 0 0
#> 192.1 16.44 1 31 1 0
#> 24.1 23.89 1 38 0 0
#> 175.1 21.91 1 43 0 0
#> 106 16.67 1 49 1 0
#> 101.3 9.97 1 10 0 1
#> 123 13.00 1 44 1 0
#> 26 15.77 1 49 0 1
#> 68 20.62 1 44 0 0
#> 43.3 12.10 1 61 0 1
#> 76 19.22 1 54 0 1
#> 168 23.72 1 70 0 0
#> 42 12.43 1 49 0 1
#> 124.1 9.73 1 NA 1 0
#> 50.1 10.02 1 NA 1 0
#> 72 24.00 0 40 0 1
#> 142 24.00 0 53 0 0
#> 20 24.00 0 46 1 0
#> 35 24.00 0 51 0 0
#> 104 24.00 0 50 1 0
#> 143 24.00 0 51 0 0
#> 185 24.00 0 44 1 0
#> 162 24.00 0 51 0 0
#> 22 24.00 0 52 1 0
#> 120 24.00 0 68 0 1
#> 196 24.00 0 19 0 0
#> 82 24.00 0 34 0 0
#> 2 24.00 0 9 0 0
#> 193 24.00 0 45 0 1
#> 161 24.00 0 45 0 0
#> 147 24.00 0 76 1 0
#> 12 24.00 0 63 0 0
#> 185.1 24.00 0 44 1 0
#> 142.1 24.00 0 53 0 0
#> 75 24.00 0 21 1 0
#> 131 24.00 0 66 0 0
#> 95 24.00 0 68 0 1
#> 162.1 24.00 0 51 0 0
#> 173 24.00 0 19 0 1
#> 172 24.00 0 41 0 0
#> 109 24.00 0 48 0 0
#> 120.1 24.00 0 68 0 1
#> 35.1 24.00 0 51 0 0
#> 148 24.00 0 61 1 0
#> 138 24.00 0 44 1 0
#> 62 24.00 0 71 0 0
#> 142.2 24.00 0 53 0 0
#> 31 24.00 0 36 0 1
#> 3 24.00 0 31 1 0
#> 156 24.00 0 50 1 0
#> 148.1 24.00 0 61 1 0
#> 173.1 24.00 0 19 0 1
#> 173.2 24.00 0 19 0 1
#> 178 24.00 0 52 1 0
#> 64 24.00 0 43 0 0
#> 198 24.00 0 66 0 1
#> 103 24.00 0 56 1 0
#> 67 24.00 0 25 0 0
#> 65 24.00 0 57 1 0
#> 9 24.00 0 31 1 0
#> 3.1 24.00 0 31 1 0
#> 20.1 24.00 0 46 1 0
#> 116 24.00 0 58 0 1
#> 9.1 24.00 0 31 1 0
#> 115 24.00 0 NA 1 0
#> 163 24.00 0 66 0 0
#> 35.2 24.00 0 51 0 0
#> 35.3 24.00 0 51 0 0
#> 82.1 24.00 0 34 0 0
#> 200 24.00 0 64 0 0
#> 53 24.00 0 32 0 1
#> 160 24.00 0 31 1 0
#> 19 24.00 0 57 0 1
#> 109.1 24.00 0 48 0 0
#> 115.1 24.00 0 NA 1 0
#> 135 24.00 0 58 1 0
#> 11 24.00 0 42 0 1
#> 71 24.00 0 51 0 0
#> 21 24.00 0 47 0 0
#> 118 24.00 0 44 1 0
#> 172.1 24.00 0 41 0 0
#> 126 24.00 0 48 0 0
#> 2.1 24.00 0 9 0 0
#> 141 24.00 0 44 1 0
#> 7 24.00 0 37 1 0
#> 3.2 24.00 0 31 1 0
#> 162.2 24.00 0 51 0 0
#> 83 24.00 0 6 0 0
#> 173.3 24.00 0 19 0 1
#> 200.1 24.00 0 64 0 0
#> 94 24.00 0 51 0 1
#> 20.2 24.00 0 46 1 0
#> 7.1 24.00 0 37 1 0
#> 182 24.00 0 35 0 0
#> 173.4 24.00 0 19 0 1
#> 144 24.00 0 28 0 1
#> 73 24.00 0 NA 0 1
#> 137 24.00 0 45 1 0
#> 9.2 24.00 0 31 1 0
#> 19.1 24.00 0 57 0 1
#> 118.1 24.00 0 44 1 0
#> 116.1 24.00 0 58 0 1
#> 151 24.00 0 42 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.707 NA NA NA
#> 2 age, Cure model 0.00933 NA NA NA
#> 3 grade_ii, Cure model 0.227 NA NA NA
#> 4 grade_iii, Cure model 1.12 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00342 NA NA NA
#> 2 grade_ii, Survival model 0.738 NA NA NA
#> 3 grade_iii, Survival model 0.692 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.707015 0.009328 0.226676 1.119351
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 256.5
#> Residual Deviance: 245.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.707014664 0.009328147 0.226675791 1.119351472
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.003421334 0.738087033 0.692344232
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.75130665 0.67433660 0.96645348 0.55917739 0.27752550 0.50129860
#> [7] 0.80787007 0.90468654 0.93627323 0.53100925 0.76416359 0.98567457
#> [13] 0.45849025 0.73159469 0.83157550 0.93627323 0.27752550 0.35265510
#> [19] 0.32237092 0.40727603 0.11656594 0.78333023 0.86072050 0.23425418
#> [25] 0.39360853 0.96645348 0.93627323 0.87772601 0.37984607 0.35265510
#> [31] 0.43387493 0.82568500 0.73159469 0.71081226 0.96645348 0.43387493
#> [37] 0.45849025 0.55917739 0.89929466 0.64307188 0.68906908 0.65896614
#> [43] 0.04844219 0.11656594 0.66670382 0.65109925 0.73159469 0.71788173
#> [49] 0.92076658 0.90468654 0.62697029 0.96145697 0.63502699 0.61038504
#> [55] 0.87772601 0.54056256 0.96645348 0.87772601 0.59372619 0.99048425
#> [61] 0.59372619 0.67433660 0.92076658 0.91542242 0.84912368 0.49069739
#> [67] 0.92076658 0.25695799 0.69636503 0.80787007 0.75130665 0.50129860
#> [73] 0.86072050 0.84912368 0.79567078 0.95641776 0.78333023 0.83157550
#> [79] 0.45849025 0.80180462 0.81973583 0.32237092 0.52121378 0.18014192
#> [85] 0.76416359 0.55917739 0.27752550 0.99525885 0.58501375 0.71788173
#> [91] 0.04844219 0.40727603 0.70364329 0.93627323 0.84329939 0.77697143
#> [97] 0.54988277 0.87772601 0.61875567 0.20767165 0.87207863 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 79 111 16 128 92 99 96 10 101 32 100 70 197
#> 16.23 17.45 8.71 20.35 22.92 21.19 14.54 10.53 9.97 20.90 16.07 7.38 21.60
#> 5 155 101.1 92.1 63 113 175 78 125 140 129 66 16.1
#> 16.43 13.08 9.97 22.92 22.77 22.86 21.91 23.88 15.65 12.68 23.41 22.13 8.71
#> 101.2 43 169 63.1 136 60 5.1 130 16.2 136.1 197.1 128.1 107
#> 9.97 12.10 22.41 22.77 21.83 13.15 16.43 16.47 8.71 21.83 21.60 20.35 11.18
#> 88 45 41 24 78.1 117 51 5.2 192 145 10.1 97 183
#> 18.37 17.42 18.02 23.89 23.88 17.46 18.23 16.43 16.44 10.07 10.53 19.14 9.24
#> 8 58 43.1 190 16.3 43.2 170 77 170.1 111.1 145.1 61 14
#> 18.43 19.34 12.10 20.81 8.71 12.10 19.54 7.27 19.54 17.45 10.07 10.12 12.89
#> 139 145.2 69 23 96.1 79.1 99.1 140.1 14.1 39 187 125.1 155.1
#> 21.49 10.07 23.23 16.92 14.54 16.23 21.19 12.68 12.89 15.59 9.92 15.65 13.08
#> 197.2 18 81 113.1 90 86 100.1 128.2 92.2 127 105 192.1 24.1
#> 21.60 15.21 14.06 22.86 20.94 23.81 16.07 20.35 22.92 3.53 19.75 16.44 23.89
#> 175.1 106 101.3 123 26 68 43.3 76 168 42 72 142 20
#> 21.91 16.67 9.97 13.00 15.77 20.62 12.10 19.22 23.72 12.43 24.00 24.00 24.00
#> 35 104 143 185 162 22 120 196 82 2 193 161 147
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12 185.1 142.1 75 131 95 162.1 173 172 109 120.1 35.1 148
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 138 62 142.2 31 3 156 148.1 173.1 173.2 178 64 198 103
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67 65 9 3.1 20.1 116 9.1 163 35.2 35.3 82.1 200 53
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 160 19 109.1 135 11 71 21 118 172.1 126 2.1 141 7
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3.2 162.2 83 173.3 200.1 94 20.2 7.1 182 173.4 144 137 9.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 19.1 118.1 116.1 151
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[79]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.004276461 0.665148787 0.399098800
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.256592068 0.006677952 -0.409384440
#> grade_iii, Cure model
#> 0.647790068
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 168 23.72 1 70 0 0
#> 179 18.63 1 42 0 0
#> 96 14.54 1 33 0 1
#> 85 16.44 1 36 0 0
#> 184 17.77 1 38 0 0
#> 89 11.44 1 NA 0 0
#> 197 21.60 1 69 1 0
#> 39 15.59 1 37 0 1
#> 70 7.38 1 30 1 0
#> 159 10.55 1 50 0 1
#> 50 10.02 1 NA 1 0
#> 175 21.91 1 43 0 0
#> 97 19.14 1 65 0 1
#> 18 15.21 1 49 1 0
#> 88 18.37 1 47 0 0
#> 66 22.13 1 53 0 0
#> 195 11.76 1 NA 1 0
#> 39.1 15.59 1 37 0 1
#> 168.1 23.72 1 70 0 0
#> 171 16.57 1 41 0 1
#> 61 10.12 1 36 0 1
#> 10 10.53 1 34 0 0
#> 188 16.16 1 46 0 1
#> 15 22.68 1 48 0 0
#> 18.1 15.21 1 49 1 0
#> 18.2 15.21 1 49 1 0
#> 177 12.53 1 75 0 0
#> 55 19.34 1 69 0 1
#> 133 14.65 1 57 0 0
#> 88.1 18.37 1 47 0 0
#> 66.1 22.13 1 53 0 0
#> 93 10.33 1 52 0 1
#> 171.1 16.57 1 41 0 1
#> 170 19.54 1 43 0 1
#> 127 3.53 1 62 0 1
#> 180 14.82 1 37 0 0
#> 51 18.23 1 83 0 1
#> 124 9.73 1 NA 1 0
#> 29 15.45 1 68 1 0
#> 128 20.35 1 35 0 1
#> 41 18.02 1 40 1 0
#> 153 21.33 1 55 1 0
#> 189 10.51 1 NA 1 0
#> 52 10.42 1 52 0 1
#> 55.1 19.34 1 69 0 1
#> 39.2 15.59 1 37 0 1
#> 52.1 10.42 1 52 0 1
#> 39.3 15.59 1 37 0 1
#> 110 17.56 1 65 0 1
#> 157 15.10 1 47 0 0
#> 154 12.63 1 20 1 0
#> 88.2 18.37 1 47 0 0
#> 97.1 19.14 1 65 0 1
#> 134 17.81 1 47 1 0
#> 42 12.43 1 49 0 1
#> 45 17.42 1 54 0 1
#> 68 20.62 1 44 0 0
#> 16 8.71 1 71 0 1
#> 58 19.34 1 39 0 0
#> 55.2 19.34 1 69 0 1
#> 145 10.07 1 65 1 0
#> 149 8.37 1 33 1 0
#> 124.1 9.73 1 NA 1 0
#> 134.1 17.81 1 47 1 0
#> 171.2 16.57 1 41 0 1
#> 43 12.10 1 61 0 1
#> 100 16.07 1 60 0 0
#> 180.1 14.82 1 37 0 0
#> 108 18.29 1 39 0 1
#> 129 23.41 1 53 1 0
#> 133.1 14.65 1 57 0 0
#> 128.1 20.35 1 35 0 1
#> 145.1 10.07 1 65 1 0
#> 45.1 17.42 1 54 0 1
#> 69 23.23 1 25 0 1
#> 124.2 9.73 1 NA 1 0
#> 86 23.81 1 58 0 1
#> 90 20.94 1 50 0 1
#> 30 17.43 1 78 0 0
#> 189.1 10.51 1 NA 1 0
#> 25 6.32 1 34 1 0
#> 101 9.97 1 10 0 1
#> 167 15.55 1 56 1 0
#> 58.1 19.34 1 39 0 0
#> 108.1 18.29 1 39 0 1
#> 167.1 15.55 1 56 1 0
#> 51.1 18.23 1 83 0 1
#> 63 22.77 1 31 1 0
#> 24 23.89 1 38 0 0
#> 92 22.92 1 47 0 1
#> 59 10.16 1 NA 1 0
#> 110.1 17.56 1 65 0 1
#> 169 22.41 1 46 0 0
#> 111 17.45 1 47 0 1
#> 40 18.00 1 28 1 0
#> 133.2 14.65 1 57 0 0
#> 108.2 18.29 1 39 0 1
#> 106 16.67 1 49 1 0
#> 157.1 15.10 1 47 0 0
#> 189.2 10.51 1 NA 1 0
#> 140 12.68 1 59 1 0
#> 175.1 21.91 1 43 0 0
#> 8 18.43 1 32 0 0
#> 123 13.00 1 44 1 0
#> 140.1 12.68 1 59 1 0
#> 40.1 18.00 1 28 1 0
#> 97.2 19.14 1 65 0 1
#> 96.1 14.54 1 33 0 1
#> 89.1 11.44 1 NA 0 0
#> 177.1 12.53 1 75 0 0
#> 199 19.81 1 NA 0 1
#> 70.1 7.38 1 30 1 0
#> 19 24.00 0 57 0 1
#> 151 24.00 0 42 0 0
#> 84 24.00 0 39 0 1
#> 147 24.00 0 76 1 0
#> 135 24.00 0 58 1 0
#> 122 24.00 0 66 0 0
#> 75 24.00 0 21 1 0
#> 73 24.00 0 NA 0 1
#> 2 24.00 0 9 0 0
#> 9 24.00 0 31 1 0
#> 3 24.00 0 31 1 0
#> 142 24.00 0 53 0 0
#> 22 24.00 0 52 1 0
#> 33 24.00 0 53 0 0
#> 148 24.00 0 61 1 0
#> 75.1 24.00 0 21 1 0
#> 121 24.00 0 57 1 0
#> 20 24.00 0 46 1 0
#> 19.1 24.00 0 57 0 1
#> 185 24.00 0 44 1 0
#> 147.1 24.00 0 76 1 0
#> 198 24.00 0 66 0 1
#> 98 24.00 0 34 1 0
#> 172 24.00 0 41 0 0
#> 137 24.00 0 45 1 0
#> 9.1 24.00 0 31 1 0
#> 34 24.00 0 36 0 0
#> 102 24.00 0 49 0 0
#> 112 24.00 0 61 0 0
#> 198.1 24.00 0 66 0 1
#> 65 24.00 0 57 1 0
#> 38 24.00 0 31 1 0
#> 161 24.00 0 45 0 0
#> 11 24.00 0 42 0 1
#> 162 24.00 0 51 0 0
#> 48 24.00 0 31 1 0
#> 120 24.00 0 68 0 1
#> 1 24.00 0 23 1 0
#> 178 24.00 0 52 1 0
#> 182 24.00 0 35 0 0
#> 84.1 24.00 0 39 0 1
#> 12 24.00 0 63 0 0
#> 62 24.00 0 71 0 0
#> 151.1 24.00 0 42 0 0
#> 31 24.00 0 36 0 1
#> 119 24.00 0 17 0 0
#> 148.1 24.00 0 61 1 0
#> 185.1 24.00 0 44 1 0
#> 74 24.00 0 43 0 1
#> 103 24.00 0 56 1 0
#> 196 24.00 0 19 0 0
#> 144 24.00 0 28 0 1
#> 193 24.00 0 45 0 1
#> 94 24.00 0 51 0 1
#> 147.2 24.00 0 76 1 0
#> 160 24.00 0 31 1 0
#> 176 24.00 0 43 0 1
#> 144.1 24.00 0 28 0 1
#> 46 24.00 0 71 0 0
#> 12.1 24.00 0 63 0 0
#> 176.1 24.00 0 43 0 1
#> 151.2 24.00 0 42 0 0
#> 80 24.00 0 41 0 0
#> 146 24.00 0 63 1 0
#> 198.2 24.00 0 66 0 1
#> 80.1 24.00 0 41 0 0
#> 38.1 24.00 0 31 1 0
#> 62.1 24.00 0 71 0 0
#> 137.1 24.00 0 45 1 0
#> 137.2 24.00 0 45 1 0
#> 132 24.00 0 55 0 0
#> 121.1 24.00 0 57 1 0
#> 146.1 24.00 0 63 1 0
#> 62.2 24.00 0 71 0 0
#> 2.1 24.00 0 9 0 0
#> 31.1 24.00 0 36 0 1
#> 121.2 24.00 0 57 1 0
#> 148.2 24.00 0 61 1 0
#> 198.3 24.00 0 66 0 1
#> 1.1 24.00 0 23 1 0
#> 74.1 24.00 0 43 0 1
#> 142.1 24.00 0 53 0 0
#> 38.2 24.00 0 31 1 0
#> 185.2 24.00 0 44 1 0
#> 28 24.00 0 67 1 0
#> 200 24.00 0 64 0 0
#> 34.1 24.00 0 36 0 0
#> 53 24.00 0 32 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.257 NA NA NA
#> 2 age, Cure model 0.00668 NA NA NA
#> 3 grade_ii, Cure model -0.409 NA NA NA
#> 4 grade_iii, Cure model 0.648 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00428 NA NA NA
#> 2 grade_ii, Survival model 0.665 NA NA NA
#> 3 grade_iii, Survival model 0.399 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.256592 0.006678 -0.409384 0.647790
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 258.3
#> Residual Deviance: 249.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.256592068 0.006677952 -0.409384440 0.647790068
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.004276461 0.665148787 0.399098800
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.034190645 0.338912584 0.781944022 0.599654129 0.493713430 0.179166249
#> [7] 0.628248880 0.966334681 0.870656533 0.155631355 0.308062774 0.692490812
#> [13] 0.360288449 0.132684724 0.628248880 0.034190645 0.571541745 0.914522662
#> [19] 0.879461244 0.609196921 0.109706261 0.692490812 0.692490812 0.835378465
#> [25] 0.257761454 0.754941371 0.360288449 0.132684724 0.905756977 0.571541745
#> [31] 0.246806620 0.991597801 0.736970500 0.422997805 0.683311566 0.225157892
#> [37] 0.443897866 0.190988279 0.888277900 0.257761454 0.628248880 0.888277900
#> [43] 0.628248880 0.503569419 0.719063550 0.826573293 0.360288449 0.308062774
#> [49] 0.474255890 0.852997382 0.542568484 0.213742173 0.949143441 0.257761454
#> [55] 0.257761454 0.923265069 0.957765628 0.474255890 0.571541745 0.861833662
#> [61] 0.618706303 0.736970500 0.391970209 0.060587402 0.754941371 0.225157892
#> [67] 0.923265069 0.542568484 0.073866666 0.020805169 0.202430198 0.532754564
#> [73] 0.983185384 0.940513400 0.664965243 0.257761454 0.391970209 0.664965243
#> [79] 0.422997805 0.098530866 0.006415691 0.086389724 0.503569419 0.121097834
#> [85] 0.522991657 0.454315303 0.754941371 0.391970209 0.561892034 0.719063550
#> [91] 0.808909768 0.155631355 0.349579609 0.799928479 0.808909768 0.454315303
#> [97] 0.308062774 0.781944022 0.835378465 0.966334681 0.000000000 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000
#>
#> $Time
#> 168 179 96 85 184 197 39 70 159 175 97 18 88
#> 23.72 18.63 14.54 16.44 17.77 21.60 15.59 7.38 10.55 21.91 19.14 15.21 18.37
#> 66 39.1 168.1 171 61 10 188 15 18.1 18.2 177 55 133
#> 22.13 15.59 23.72 16.57 10.12 10.53 16.16 22.68 15.21 15.21 12.53 19.34 14.65
#> 88.1 66.1 93 171.1 170 127 180 51 29 128 41 153 52
#> 18.37 22.13 10.33 16.57 19.54 3.53 14.82 18.23 15.45 20.35 18.02 21.33 10.42
#> 55.1 39.2 52.1 39.3 110 157 154 88.2 97.1 134 42 45 68
#> 19.34 15.59 10.42 15.59 17.56 15.10 12.63 18.37 19.14 17.81 12.43 17.42 20.62
#> 16 58 55.2 145 149 134.1 171.2 43 100 180.1 108 129 133.1
#> 8.71 19.34 19.34 10.07 8.37 17.81 16.57 12.10 16.07 14.82 18.29 23.41 14.65
#> 128.1 145.1 45.1 69 86 90 30 25 101 167 58.1 108.1 167.1
#> 20.35 10.07 17.42 23.23 23.81 20.94 17.43 6.32 9.97 15.55 19.34 18.29 15.55
#> 51.1 63 24 92 110.1 169 111 40 133.2 108.2 106 157.1 140
#> 18.23 22.77 23.89 22.92 17.56 22.41 17.45 18.00 14.65 18.29 16.67 15.10 12.68
#> 175.1 8 123 140.1 40.1 97.2 96.1 177.1 70.1 19 151 84 147
#> 21.91 18.43 13.00 12.68 18.00 19.14 14.54 12.53 7.38 24.00 24.00 24.00 24.00
#> 135 122 75 2 9 3 142 22 33 148 75.1 121 20
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 19.1 185 147.1 198 98 172 137 9.1 34 102 112 198.1 65
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 38 161 11 162 48 120 1 178 182 84.1 12 62 151.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31 119 148.1 185.1 74 103 196 144 193 94 147.2 160 176
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 144.1 46 12.1 176.1 151.2 80 146 198.2 80.1 38.1 62.1 137.1 137.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 132 121.1 146.1 62.2 2.1 31.1 121.2 148.2 198.3 1.1 74.1 142.1 38.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185.2 28 200 34.1 53
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[80]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01424552 0.55957862 0.05985955
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.09859998 0.00437587 -0.14777208
#> grade_iii, Cure model
#> 0.34625928
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 140 12.68 1 59 1 0
#> 10 10.53 1 34 0 0
#> 58 19.34 1 39 0 0
#> 79 16.23 1 54 1 0
#> 127 3.53 1 62 0 1
#> 192 16.44 1 31 1 0
#> 25 6.32 1 34 1 0
#> 179 18.63 1 42 0 0
#> 5 16.43 1 51 0 1
#> 157 15.10 1 47 0 0
#> 188 16.16 1 46 0 1
#> 5.1 16.43 1 51 0 1
#> 39 15.59 1 37 0 1
#> 164 23.60 1 76 0 1
#> 26 15.77 1 49 0 1
#> 68 20.62 1 44 0 0
#> 134 17.81 1 47 1 0
#> 124 9.73 1 NA 1 0
#> 13 14.34 1 54 0 1
#> 158 20.14 1 74 1 0
#> 184 17.77 1 38 0 0
#> 133 14.65 1 57 0 0
#> 123 13.00 1 44 1 0
#> 51 18.23 1 83 0 1
#> 92 22.92 1 47 0 1
#> 70 7.38 1 30 1 0
#> 4 17.64 1 NA 0 1
#> 197 21.60 1 69 1 0
#> 55 19.34 1 69 0 1
#> 59 10.16 1 NA 1 0
#> 79.1 16.23 1 54 1 0
#> 14 12.89 1 21 0 0
#> 110 17.56 1 65 0 1
#> 81 14.06 1 34 0 0
#> 170 19.54 1 43 0 1
#> 93 10.33 1 52 0 1
#> 50 10.02 1 NA 1 0
#> 26.1 15.77 1 49 0 1
#> 124.1 9.73 1 NA 1 0
#> 86 23.81 1 58 0 1
#> 45 17.42 1 54 0 1
#> 180 14.82 1 37 0 0
#> 15 22.68 1 48 0 0
#> 85 16.44 1 36 0 0
#> 92.1 22.92 1 47 0 1
#> 70.1 7.38 1 30 1 0
#> 42 12.43 1 49 0 1
#> 155 13.08 1 26 0 0
#> 164.1 23.60 1 76 0 1
#> 134.1 17.81 1 47 1 0
#> 4.1 17.64 1 NA 0 1
#> 180.1 14.82 1 37 0 0
#> 169 22.41 1 46 0 0
#> 134.2 17.81 1 47 1 0
#> 55.1 19.34 1 69 0 1
#> 52 10.42 1 52 0 1
#> 181 16.46 1 45 0 1
#> 70.2 7.38 1 30 1 0
#> 175 21.91 1 43 0 0
#> 130 16.47 1 53 0 1
#> 63 22.77 1 31 1 0
#> 181.1 16.46 1 45 0 1
#> 56 12.21 1 60 0 0
#> 41 18.02 1 40 1 0
#> 91 5.33 1 61 0 1
#> 91.1 5.33 1 61 0 1
#> 100 16.07 1 60 0 0
#> 124.2 9.73 1 NA 1 0
#> 92.2 22.92 1 47 0 1
#> 128 20.35 1 35 0 1
#> 97 19.14 1 65 0 1
#> 18 15.21 1 49 1 0
#> 150 20.33 1 48 0 0
#> 58.1 19.34 1 39 0 0
#> 153 21.33 1 55 1 0
#> 36 21.19 1 48 0 1
#> 128.1 20.35 1 35 0 1
#> 78 23.88 1 43 0 0
#> 24 23.89 1 38 0 0
#> 180.2 14.82 1 37 0 0
#> 50.1 10.02 1 NA 1 0
#> 55.2 19.34 1 69 0 1
#> 81.1 14.06 1 34 0 0
#> 69 23.23 1 25 0 1
#> 14.1 12.89 1 21 0 0
#> 130.1 16.47 1 53 0 1
#> 90 20.94 1 50 0 1
#> 171 16.57 1 41 0 1
#> 199 19.81 1 NA 0 1
#> 125 15.65 1 67 1 0
#> 42.1 12.43 1 49 0 1
#> 168 23.72 1 70 0 0
#> 123.1 13.00 1 44 1 0
#> 149 8.37 1 33 1 0
#> 153.1 21.33 1 55 1 0
#> 100.1 16.07 1 60 0 0
#> 139 21.49 1 63 1 0
#> 29 15.45 1 68 1 0
#> 107 11.18 1 54 1 0
#> 111 17.45 1 47 0 1
#> 26.2 15.77 1 49 0 1
#> 155.1 13.08 1 26 0 0
#> 14.2 12.89 1 21 0 0
#> 30 17.43 1 78 0 0
#> 180.3 14.82 1 37 0 0
#> 37 12.52 1 57 1 0
#> 180.4 14.82 1 37 0 0
#> 187 9.92 1 39 1 0
#> 68.1 20.62 1 44 0 0
#> 29.1 15.45 1 68 1 0
#> 37.1 12.52 1 57 1 0
#> 29.2 15.45 1 68 1 0
#> 64 24.00 0 43 0 0
#> 112 24.00 0 61 0 0
#> 116 24.00 0 58 0 1
#> 20 24.00 0 46 1 0
#> 38 24.00 0 31 1 0
#> 151 24.00 0 42 0 0
#> 126 24.00 0 48 0 0
#> 64.1 24.00 0 43 0 0
#> 22 24.00 0 52 1 0
#> 115 24.00 0 NA 1 0
#> 35 24.00 0 51 0 0
#> 98 24.00 0 34 1 0
#> 74 24.00 0 43 0 1
#> 17 24.00 0 38 0 1
#> 174 24.00 0 49 1 0
#> 165 24.00 0 47 0 0
#> 7 24.00 0 37 1 0
#> 148 24.00 0 61 1 0
#> 102 24.00 0 49 0 0
#> 54 24.00 0 53 1 0
#> 9 24.00 0 31 1 0
#> 19 24.00 0 57 0 1
#> 118 24.00 0 44 1 0
#> 17.1 24.00 0 38 0 1
#> 17.2 24.00 0 38 0 1
#> 27 24.00 0 63 1 0
#> 176 24.00 0 43 0 1
#> 198 24.00 0 66 0 1
#> 191 24.00 0 60 0 1
#> 126.1 24.00 0 48 0 0
#> 152 24.00 0 36 0 1
#> 172 24.00 0 41 0 0
#> 119 24.00 0 17 0 0
#> 116.1 24.00 0 58 0 1
#> 54.1 24.00 0 53 1 0
#> 172.1 24.00 0 41 0 0
#> 1 24.00 0 23 1 0
#> 72 24.00 0 40 0 1
#> 173 24.00 0 19 0 1
#> 122 24.00 0 66 0 0
#> 138 24.00 0 44 1 0
#> 146 24.00 0 63 1 0
#> 38.1 24.00 0 31 1 0
#> 31 24.00 0 36 0 1
#> 104 24.00 0 50 1 0
#> 65 24.00 0 57 1 0
#> 200 24.00 0 64 0 0
#> 94 24.00 0 51 0 1
#> 151.1 24.00 0 42 0 0
#> 47 24.00 0 38 0 1
#> 2 24.00 0 9 0 0
#> 141 24.00 0 44 1 0
#> 172.2 24.00 0 41 0 0
#> 162 24.00 0 51 0 0
#> 131 24.00 0 66 0 0
#> 28 24.00 0 67 1 0
#> 87 24.00 0 27 0 0
#> 174.1 24.00 0 49 1 0
#> 47.1 24.00 0 38 0 1
#> 144 24.00 0 28 0 1
#> 121 24.00 0 57 1 0
#> 64.2 24.00 0 43 0 0
#> 142 24.00 0 53 0 0
#> 176.1 24.00 0 43 0 1
#> 74.1 24.00 0 43 0 1
#> 115.1 24.00 0 NA 1 0
#> 44 24.00 0 56 0 0
#> 9.1 24.00 0 31 1 0
#> 103 24.00 0 56 1 0
#> 95 24.00 0 68 0 1
#> 95.1 24.00 0 68 0 1
#> 7.1 24.00 0 37 1 0
#> 87.1 24.00 0 27 0 0
#> 62 24.00 0 71 0 0
#> 28.1 24.00 0 67 1 0
#> 112.1 24.00 0 61 0 0
#> 162.1 24.00 0 51 0 0
#> 104.1 24.00 0 50 1 0
#> 116.2 24.00 0 58 0 1
#> 121.1 24.00 0 57 1 0
#> 182 24.00 0 35 0 0
#> 20.1 24.00 0 46 1 0
#> 178 24.00 0 52 1 0
#> 44.1 24.00 0 56 0 0
#> 198.1 24.00 0 66 0 1
#> 112.2 24.00 0 61 0 0
#> 185 24.00 0 44 1 0
#> 191.1 24.00 0 60 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.0986 NA NA NA
#> 2 age, Cure model 0.00438 NA NA NA
#> 3 grade_ii, Cure model -0.148 NA NA NA
#> 4 grade_iii, Cure model 0.346 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0142 NA NA NA
#> 2 grade_ii, Survival model 0.560 NA NA NA
#> 3 grade_iii, Survival model 0.0599 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.098600 0.004376 -0.147772 0.346259
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.5
#> Residual Deviance: 258.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.09859998 0.00437587 -0.14777208 0.34625928
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01424552 0.55957862 0.05985955
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 7.207567e-01 8.210389e-01 1.083725e-01 3.353342e-01 9.847312e-01
#> [6] 2.940300e-01 9.398106e-01 1.506333e-01 3.143520e-01 4.962340e-01
#> [11] 3.565681e-01 3.143520e-01 4.359535e-01 4.007663e-03 3.897779e-01
#> [16] 6.608324e-02 1.754728e-01 5.844020e-01 9.526991e-02 1.997779e-01
#> [21] 5.711607e-01 6.520612e-01 1.587198e-01 1.133351e-02 8.958230e-01
#> [26] 3.664843e-02 1.083725e-01 3.353342e-01 6.794502e-01 2.083846e-01
#> [31] 5.977975e-01 1.017316e-01 8.507286e-01 3.897779e-01 1.281320e-03
#> [36] 2.354170e-01 5.087212e-01 2.413433e-02 2.940300e-01 1.133351e-02
#> [41] 8.958230e-01 7.630486e-01 6.247469e-01 4.007663e-03 1.754728e-01
#> [46] 5.087212e-01 2.803120e-02 1.754728e-01 1.083725e-01 8.358186e-01
#> [51] 2.739005e-01 8.958230e-01 3.220771e-02 2.544029e-01 2.052657e-02
#> [56] 2.739005e-01 7.917326e-01 1.670941e-01 9.546896e-01 9.546896e-01
#> [61] 3.674963e-01 1.133351e-02 7.722705e-02 1.427377e-01 4.838983e-01
#> [66] 8.897491e-02 1.083725e-01 4.607314e-02 5.553373e-02 7.722705e-02
#> [71] 5.263238e-04 9.440808e-05 5.087212e-01 1.083725e-01 5.977975e-01
#> [76] 8.460360e-03 6.794502e-01 2.544029e-01 6.069863e-02 2.448349e-01
#> [81] 4.240868e-01 7.630486e-01 2.404554e-03 6.520612e-01 8.808078e-01
#> [86] 4.607314e-02 3.674963e-01 4.128349e-02 4.479421e-01 8.063605e-01
#> [91] 2.172024e-01 3.897779e-01 6.247469e-01 6.794502e-01 2.261867e-01
#> [96] 5.087212e-01 7.348646e-01 5.087212e-01 8.657687e-01 6.608324e-02
#> [101] 4.479421e-01 7.348646e-01 4.479421e-01 0.000000e+00 0.000000e+00
#> [106] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [186] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#>
#> $Time
#> 140 10 58 79 127 192 25 179 5 157 188 5.1 39
#> 12.68 10.53 19.34 16.23 3.53 16.44 6.32 18.63 16.43 15.10 16.16 16.43 15.59
#> 164 26 68 134 13 158 184 133 123 51 92 70 197
#> 23.60 15.77 20.62 17.81 14.34 20.14 17.77 14.65 13.00 18.23 22.92 7.38 21.60
#> 55 79.1 14 110 81 170 93 26.1 86 45 180 15 85
#> 19.34 16.23 12.89 17.56 14.06 19.54 10.33 15.77 23.81 17.42 14.82 22.68 16.44
#> 92.1 70.1 42 155 164.1 134.1 180.1 169 134.2 55.1 52 181 70.2
#> 22.92 7.38 12.43 13.08 23.60 17.81 14.82 22.41 17.81 19.34 10.42 16.46 7.38
#> 175 130 63 181.1 56 41 91 91.1 100 92.2 128 97 18
#> 21.91 16.47 22.77 16.46 12.21 18.02 5.33 5.33 16.07 22.92 20.35 19.14 15.21
#> 150 58.1 153 36 128.1 78 24 180.2 55.2 81.1 69 14.1 130.1
#> 20.33 19.34 21.33 21.19 20.35 23.88 23.89 14.82 19.34 14.06 23.23 12.89 16.47
#> 90 171 125 42.1 168 123.1 149 153.1 100.1 139 29 107 111
#> 20.94 16.57 15.65 12.43 23.72 13.00 8.37 21.33 16.07 21.49 15.45 11.18 17.45
#> 26.2 155.1 14.2 30 180.3 37 180.4 187 68.1 29.1 37.1 29.2 64
#> 15.77 13.08 12.89 17.43 14.82 12.52 14.82 9.92 20.62 15.45 12.52 15.45 24.00
#> 112 116 20 38 151 126 64.1 22 35 98 74 17 174
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165 7 148 102 54 9 19 118 17.1 17.2 27 176 198
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 191 126.1 152 172 119 116.1 54.1 172.1 1 72 173 122 138
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 146 38.1 31 104 65 200 94 151.1 47 2 141 172.2 162
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131 28 87 174.1 47.1 144 121 64.2 142 176.1 74.1 44 9.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103 95 95.1 7.1 87.1 62 28.1 112.1 162.1 104.1 116.2 121.1 182
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20.1 178 44.1 198.1 112.2 185 191.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[81]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.01663864 0.45682172 0.25670363
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.210463322 0.003492557 -0.396234951
#> grade_iii, Cure model
#> 0.928731552
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 55 19.34 1 69 0 1
#> 179 18.63 1 42 0 0
#> 30 17.43 1 78 0 0
#> 45 17.42 1 54 0 1
#> 125 15.65 1 67 1 0
#> 106 16.67 1 49 1 0
#> 93 10.33 1 52 0 1
#> 40 18.00 1 28 1 0
#> 52 10.42 1 52 0 1
#> 43 12.10 1 61 0 1
#> 37 12.52 1 57 1 0
#> 140 12.68 1 59 1 0
#> 155 13.08 1 26 0 0
#> 13 14.34 1 54 0 1
#> 8 18.43 1 32 0 0
#> 157 15.10 1 47 0 0
#> 23 16.92 1 61 0 0
#> 157.1 15.10 1 47 0 0
#> 105 19.75 1 60 0 0
#> 10 10.53 1 34 0 0
#> 117 17.46 1 26 0 1
#> 136 21.83 1 43 0 1
#> 16 8.71 1 71 0 1
#> 150 20.33 1 48 0 0
#> 199 19.81 1 NA 0 1
#> 194 22.40 1 38 0 1
#> 42 12.43 1 49 0 1
#> 51 18.23 1 83 0 1
#> 18 15.21 1 49 1 0
#> 8.1 18.43 1 32 0 0
#> 101 9.97 1 10 0 1
#> 100 16.07 1 60 0 0
#> 40.1 18.00 1 28 1 0
#> 56 12.21 1 60 0 0
#> 170 19.54 1 43 0 1
#> 114 13.68 1 NA 0 0
#> 183 9.24 1 67 1 0
#> 99 21.19 1 38 0 1
#> 70 7.38 1 30 1 0
#> 50 10.02 1 NA 1 0
#> 78 23.88 1 43 0 0
#> 188 16.16 1 46 0 1
#> 179.1 18.63 1 42 0 0
#> 195 11.76 1 NA 1 0
#> 40.2 18.00 1 28 1 0
#> 100.1 16.07 1 60 0 0
#> 123 13.00 1 44 1 0
#> 39 15.59 1 37 0 1
#> 39.1 15.59 1 37 0 1
#> 6 15.64 1 39 0 0
#> 69 23.23 1 25 0 1
#> 57 14.46 1 45 0 1
#> 189 10.51 1 NA 1 0
#> 55.1 19.34 1 69 0 1
#> 195.1 11.76 1 NA 1 0
#> 194.1 22.40 1 38 0 1
#> 24 23.89 1 38 0 0
#> 177 12.53 1 75 0 0
#> 96 14.54 1 33 0 1
#> 40.3 18.00 1 28 1 0
#> 79 16.23 1 54 1 0
#> 23.1 16.92 1 61 0 0
#> 114.1 13.68 1 NA 0 0
#> 90 20.94 1 50 0 1
#> 26 15.77 1 49 0 1
#> 192 16.44 1 31 1 0
#> 89 11.44 1 NA 0 0
#> 159 10.55 1 50 0 1
#> 91 5.33 1 61 0 1
#> 36 21.19 1 48 0 1
#> 18.1 15.21 1 49 1 0
#> 189.1 10.51 1 NA 1 0
#> 129 23.41 1 53 1 0
#> 76 19.22 1 54 0 1
#> 18.2 15.21 1 49 1 0
#> 56.1 12.21 1 60 0 0
#> 4 17.64 1 NA 0 1
#> 194.2 22.40 1 38 0 1
#> 114.2 13.68 1 NA 0 0
#> 91.1 5.33 1 61 0 1
#> 169 22.41 1 46 0 0
#> 192.1 16.44 1 31 1 0
#> 18.3 15.21 1 49 1 0
#> 100.2 16.07 1 60 0 0
#> 30.1 17.43 1 78 0 0
#> 15 22.68 1 48 0 0
#> 166 19.98 1 48 0 0
#> 25 6.32 1 34 1 0
#> 89.1 11.44 1 NA 0 0
#> 32 20.90 1 37 1 0
#> 61 10.12 1 36 0 1
#> 108 18.29 1 39 0 1
#> 129.1 23.41 1 53 1 0
#> 13.1 14.34 1 54 0 1
#> 110 17.56 1 65 0 1
#> 150.1 20.33 1 48 0 0
#> 76.1 19.22 1 54 0 1
#> 189.2 10.51 1 NA 1 0
#> 175 21.91 1 43 0 0
#> 199.1 19.81 1 NA 0 1
#> 50.1 10.02 1 NA 1 0
#> 177.1 12.53 1 75 0 0
#> 181 16.46 1 45 0 1
#> 170.1 19.54 1 43 0 1
#> 59 10.16 1 NA 1 0
#> 68 20.62 1 44 0 0
#> 23.2 16.92 1 61 0 0
#> 36.1 21.19 1 48 0 1
#> 107 11.18 1 54 1 0
#> 6.1 15.64 1 39 0 0
#> 130 16.47 1 53 0 1
#> 39.2 15.59 1 37 0 1
#> 27 24.00 0 63 1 0
#> 17 24.00 0 38 0 1
#> 17.1 24.00 0 38 0 1
#> 173 24.00 0 19 0 1
#> 172 24.00 0 41 0 0
#> 191 24.00 0 60 0 1
#> 122 24.00 0 66 0 0
#> 20 24.00 0 46 1 0
#> 104 24.00 0 50 1 0
#> 53 24.00 0 32 0 1
#> 109 24.00 0 48 0 0
#> 112 24.00 0 61 0 0
#> 65 24.00 0 57 1 0
#> 135 24.00 0 58 1 0
#> 46 24.00 0 71 0 0
#> 185 24.00 0 44 1 0
#> 116 24.00 0 58 0 1
#> 161 24.00 0 45 0 0
#> 64 24.00 0 43 0 0
#> 132 24.00 0 55 0 0
#> 178 24.00 0 52 1 0
#> 38 24.00 0 31 1 0
#> 156 24.00 0 50 1 0
#> 121 24.00 0 57 1 0
#> 138 24.00 0 44 1 0
#> 193 24.00 0 45 0 1
#> 84 24.00 0 39 0 1
#> 126 24.00 0 48 0 0
#> 95 24.00 0 68 0 1
#> 44 24.00 0 56 0 0
#> 27.1 24.00 0 63 1 0
#> 185.1 24.00 0 44 1 0
#> 156.1 24.00 0 50 1 0
#> 186 24.00 0 45 1 0
#> 165 24.00 0 47 0 0
#> 65.1 24.00 0 57 1 0
#> 118 24.00 0 44 1 0
#> 176 24.00 0 43 0 1
#> 11 24.00 0 42 0 1
#> 44.1 24.00 0 56 0 0
#> 112.1 24.00 0 61 0 0
#> 1 24.00 0 23 1 0
#> 34 24.00 0 36 0 0
#> 28 24.00 0 67 1 0
#> 73 24.00 0 NA 0 1
#> 143 24.00 0 51 0 0
#> 35 24.00 0 51 0 0
#> 118.1 24.00 0 44 1 0
#> 135.1 24.00 0 58 1 0
#> 21 24.00 0 47 0 0
#> 161.1 24.00 0 45 0 0
#> 138.1 24.00 0 44 1 0
#> 104.1 24.00 0 50 1 0
#> 137 24.00 0 45 1 0
#> 35.1 24.00 0 51 0 0
#> 138.2 24.00 0 44 1 0
#> 31 24.00 0 36 0 1
#> 115 24.00 0 NA 1 0
#> 62 24.00 0 71 0 0
#> 132.1 24.00 0 55 0 0
#> 9 24.00 0 31 1 0
#> 48 24.00 0 31 1 0
#> 17.2 24.00 0 38 0 1
#> 122.1 24.00 0 66 0 0
#> 182 24.00 0 35 0 0
#> 47 24.00 0 38 0 1
#> 12 24.00 0 63 0 0
#> 75 24.00 0 21 1 0
#> 46.1 24.00 0 71 0 0
#> 182.1 24.00 0 35 0 0
#> 67 24.00 0 25 0 0
#> 132.2 24.00 0 55 0 0
#> 1.1 24.00 0 23 1 0
#> 35.2 24.00 0 51 0 0
#> 44.2 24.00 0 56 0 0
#> 94 24.00 0 51 0 1
#> 9.1 24.00 0 31 1 0
#> 116.1 24.00 0 58 0 1
#> 75.1 24.00 0 21 1 0
#> 54 24.00 0 53 1 0
#> 17.3 24.00 0 38 0 1
#> 20.1 24.00 0 46 1 0
#> 174 24.00 0 49 1 0
#> 148 24.00 0 61 1 0
#> 172.1 24.00 0 41 0 0
#> 143.1 24.00 0 51 0 0
#> 178.1 24.00 0 52 1 0
#> 132.3 24.00 0 55 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.210 NA NA NA
#> 2 age, Cure model 0.00349 NA NA NA
#> 3 grade_ii, Cure model -0.396 NA NA NA
#> 4 grade_iii, Cure model 0.929 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0166 NA NA NA
#> 2 grade_ii, Survival model 0.457 NA NA NA
#> 3 grade_iii, Survival model 0.257 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.210463 0.003493 -0.396235 0.928732
#>
#> Degrees of Freedom: 181 Total (i.e. Null); 178 Residual
#> Null Deviance: 251.8
#> Residual Deviance: 239.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.210463322 0.003492557 -0.396234951 0.928731552
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.01663864 0.45682172 0.25670363
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.6081151 0.6429166 0.7330493 0.7460892 0.8323042 0.7708118 0.9662369
#> [8] 0.6911133 0.9623293 0.9464158 0.9299589 0.9171750 0.9083250 0.8994242
#> [15] 0.6593556 0.8810279 0.7525153 0.8810279 0.5778780 0.9583887 0.7261731
#> [22] 0.4546746 0.9816018 0.5449840 0.3890614 0.9341351 0.6834967 0.8624224
#> [29] 0.6593556 0.9739662 0.8111154 0.6911133 0.9382757 0.5884026 0.9778124
#> [36] 0.4701523 0.9853448 0.2090465 0.8055882 0.6429166 0.6911133 0.8111154
#> [43] 0.9127745 0.8476073 0.8476073 0.8374537 0.3206307 0.8948644 0.6081151
#> [50] 0.3890614 0.1228755 0.9215087 0.8902639 0.6911133 0.7999928 0.7525153
#> [57] 0.5087191 0.8270303 0.7886129 0.9544356 0.9927607 0.4701523 0.8624224
#> [64] 0.2696713 0.6260412 0.8624224 0.9382757 0.3890614 0.9927607 0.3679069
#> [71] 0.7886129 0.8624224 0.8111154 0.7330493 0.3452557 0.5670143 0.9890651
#> [78] 0.5212725 0.9701119 0.6755115 0.2696713 0.8994242 0.7192317 0.5449840
#> [85] 0.6260412 0.4382798 0.9215087 0.7827629 0.5884026 0.5332705 0.7525153
#> [92] 0.4701523 0.9504501 0.8374537 0.7768361 0.8476073 0.0000000 0.0000000
#> [99] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [106] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#>
#> $Time
#> 55 179 30 45 125 106 93 40 52 43 37 140 155
#> 19.34 18.63 17.43 17.42 15.65 16.67 10.33 18.00 10.42 12.10 12.52 12.68 13.08
#> 13 8 157 23 157.1 105 10 117 136 16 150 194 42
#> 14.34 18.43 15.10 16.92 15.10 19.75 10.53 17.46 21.83 8.71 20.33 22.40 12.43
#> 51 18 8.1 101 100 40.1 56 170 183 99 70 78 188
#> 18.23 15.21 18.43 9.97 16.07 18.00 12.21 19.54 9.24 21.19 7.38 23.88 16.16
#> 179.1 40.2 100.1 123 39 39.1 6 69 57 55.1 194.1 24 177
#> 18.63 18.00 16.07 13.00 15.59 15.59 15.64 23.23 14.46 19.34 22.40 23.89 12.53
#> 96 40.3 79 23.1 90 26 192 159 91 36 18.1 129 76
#> 14.54 18.00 16.23 16.92 20.94 15.77 16.44 10.55 5.33 21.19 15.21 23.41 19.22
#> 18.2 56.1 194.2 91.1 169 192.1 18.3 100.2 30.1 15 166 25 32
#> 15.21 12.21 22.40 5.33 22.41 16.44 15.21 16.07 17.43 22.68 19.98 6.32 20.90
#> 61 108 129.1 13.1 110 150.1 76.1 175 177.1 181 170.1 68 23.2
#> 10.12 18.29 23.41 14.34 17.56 20.33 19.22 21.91 12.53 16.46 19.54 20.62 16.92
#> 36.1 107 6.1 130 39.2 27 17 17.1 173 172 191 122 20
#> 21.19 11.18 15.64 16.47 15.59 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 104 53 109 112 65 135 46 185 116 161 64 132 178
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 38 156 121 138 193 84 126 95 44 27.1 185.1 156.1 186
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165 65.1 118 176 11 44.1 112.1 1 34 28 143 35 118.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135.1 21 161.1 138.1 104.1 137 35.1 138.2 31 62 132.1 9 48
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 17.2 122.1 182 47 12 75 46.1 182.1 67 132.2 1.1 35.2 44.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94 9.1 116.1 75.1 54 17.3 20.1 174 148 172.1 143.1 178.1 132.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[82]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.006596554 0.504681838 0.112986752
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.6532963 0.0100777 0.3838736
#> grade_iii, Cure model
#> 0.9875037
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 29 15.45 1 68 1 0
#> 140 12.68 1 59 1 0
#> 76 19.22 1 54 0 1
#> 197 21.60 1 69 1 0
#> 86 23.81 1 58 0 1
#> 50 10.02 1 NA 1 0
#> 86.1 23.81 1 58 0 1
#> 157 15.10 1 47 0 0
#> 101 9.97 1 10 0 1
#> 70 7.38 1 30 1 0
#> 15 22.68 1 48 0 0
#> 88 18.37 1 47 0 0
#> 8 18.43 1 32 0 0
#> 101.1 9.97 1 10 0 1
#> 195 11.76 1 NA 1 0
#> 25 6.32 1 34 1 0
#> 111 17.45 1 47 0 1
#> 58 19.34 1 39 0 0
#> 41 18.02 1 40 1 0
#> 76.1 19.22 1 54 0 1
#> 149 8.37 1 33 1 0
#> 43 12.10 1 61 0 1
#> 29.1 15.45 1 68 1 0
#> 180 14.82 1 37 0 0
#> 69 23.23 1 25 0 1
#> 108 18.29 1 39 0 1
#> 30 17.43 1 78 0 0
#> 51 18.23 1 83 0 1
#> 164 23.60 1 76 0 1
#> 181 16.46 1 45 0 1
#> 97 19.14 1 65 0 1
#> 68 20.62 1 44 0 0
#> 96 14.54 1 33 0 1
#> 184 17.77 1 38 0 0
#> 42 12.43 1 49 0 1
#> 70.1 7.38 1 30 1 0
#> 45 17.42 1 54 0 1
#> 10 10.53 1 34 0 0
#> 127 3.53 1 62 0 1
#> 29.2 15.45 1 68 1 0
#> 100 16.07 1 60 0 0
#> 52 10.42 1 52 0 1
#> 25.1 6.32 1 34 1 0
#> 49 12.19 1 48 1 0
#> 154 12.63 1 20 1 0
#> 89 11.44 1 NA 0 0
#> 25.2 6.32 1 34 1 0
#> 189 10.51 1 NA 1 0
#> 15.1 22.68 1 48 0 0
#> 100.1 16.07 1 60 0 0
#> 106 16.67 1 49 1 0
#> 192 16.44 1 31 1 0
#> 184.1 17.77 1 38 0 0
#> 24 23.89 1 38 0 0
#> 199 19.81 1 NA 0 1
#> 170 19.54 1 43 0 1
#> 99 21.19 1 38 0 1
#> 179 18.63 1 42 0 0
#> 128 20.35 1 35 0 1
#> 114 13.68 1 NA 0 0
#> 32 20.90 1 37 1 0
#> 78 23.88 1 43 0 0
#> 184.2 17.77 1 38 0 0
#> 29.3 15.45 1 68 1 0
#> 57 14.46 1 45 0 1
#> 164.1 23.60 1 76 0 1
#> 81 14.06 1 34 0 0
#> 166 19.98 1 48 0 0
#> 10.1 10.53 1 34 0 0
#> 171 16.57 1 41 0 1
#> 52.1 10.42 1 52 0 1
#> 128.1 20.35 1 35 0 1
#> 8.1 18.43 1 32 0 0
#> 85 16.44 1 36 0 0
#> 188 16.16 1 46 0 1
#> 56 12.21 1 60 0 0
#> 88.1 18.37 1 47 0 0
#> 29.4 15.45 1 68 1 0
#> 8.2 18.43 1 32 0 0
#> 167 15.55 1 56 1 0
#> 16 8.71 1 71 0 1
#> 39 15.59 1 37 0 1
#> 30.1 17.43 1 78 0 0
#> 91 5.33 1 61 0 1
#> 23 16.92 1 61 0 0
#> 45.1 17.42 1 54 0 1
#> 177 12.53 1 75 0 0
#> 150 20.33 1 48 0 0
#> 113 22.86 1 34 0 0
#> 153 21.33 1 55 1 0
#> 60 13.15 1 38 1 0
#> 13 14.34 1 54 0 1
#> 169 22.41 1 46 0 0
#> 153.1 21.33 1 55 1 0
#> 180.1 14.82 1 37 0 0
#> 32.1 20.90 1 37 1 0
#> 57.1 14.46 1 45 0 1
#> 97.1 19.14 1 65 0 1
#> 128.2 20.35 1 35 0 1
#> 99.1 21.19 1 38 0 1
#> 123 13.00 1 44 1 0
#> 56.1 12.21 1 60 0 0
#> 69.1 23.23 1 25 0 1
#> 158 20.14 1 74 1 0
#> 157.1 15.10 1 47 0 0
#> 43.1 12.10 1 61 0 1
#> 145 10.07 1 65 1 0
#> 192.1 16.44 1 31 1 0
#> 145.1 10.07 1 65 1 0
#> 13.1 14.34 1 54 0 1
#> 197.1 21.60 1 69 1 0
#> 129 23.41 1 53 1 0
#> 126 24.00 0 48 0 0
#> 95 24.00 0 68 0 1
#> 193 24.00 0 45 0 1
#> 64 24.00 0 43 0 0
#> 31 24.00 0 36 0 1
#> 2 24.00 0 9 0 0
#> 87 24.00 0 27 0 0
#> 47 24.00 0 38 0 1
#> 2.1 24.00 0 9 0 0
#> 138 24.00 0 44 1 0
#> 141 24.00 0 44 1 0
#> 148 24.00 0 61 1 0
#> 178 24.00 0 52 1 0
#> 21 24.00 0 47 0 0
#> 71 24.00 0 51 0 0
#> 142 24.00 0 53 0 0
#> 62 24.00 0 71 0 0
#> 132 24.00 0 55 0 0
#> 98 24.00 0 34 1 0
#> 94 24.00 0 51 0 1
#> 80 24.00 0 41 0 0
#> 82 24.00 0 34 0 0
#> 173 24.00 0 19 0 1
#> 122 24.00 0 66 0 0
#> 186 24.00 0 45 1 0
#> 83 24.00 0 6 0 0
#> 53 24.00 0 32 0 1
#> 185 24.00 0 44 1 0
#> 33 24.00 0 53 0 0
#> 200 24.00 0 64 0 0
#> 165 24.00 0 47 0 0
#> 115 24.00 0 NA 1 0
#> 126.1 24.00 0 48 0 0
#> 21.1 24.00 0 47 0 0
#> 2.2 24.00 0 9 0 0
#> 143 24.00 0 51 0 0
#> 144 24.00 0 28 0 1
#> 161 24.00 0 45 0 0
#> 104 24.00 0 50 1 0
#> 53.1 24.00 0 32 0 1
#> 163 24.00 0 66 0 0
#> 172 24.00 0 41 0 0
#> 73 24.00 0 NA 0 1
#> 11 24.00 0 42 0 1
#> 48 24.00 0 31 1 0
#> 172.1 24.00 0 41 0 0
#> 122.1 24.00 0 66 0 0
#> 196 24.00 0 19 0 0
#> 98.1 24.00 0 34 1 0
#> 12 24.00 0 63 0 0
#> 116 24.00 0 58 0 1
#> 141.1 24.00 0 44 1 0
#> 186.1 24.00 0 45 1 0
#> 62.1 24.00 0 71 0 0
#> 115.1 24.00 0 NA 1 0
#> 82.1 24.00 0 34 0 0
#> 132.1 24.00 0 55 0 0
#> 21.2 24.00 0 47 0 0
#> 3 24.00 0 31 1 0
#> 112 24.00 0 61 0 0
#> 122.2 24.00 0 66 0 0
#> 147 24.00 0 76 1 0
#> 163.1 24.00 0 66 0 0
#> 82.2 24.00 0 34 0 0
#> 173.1 24.00 0 19 0 1
#> 20 24.00 0 46 1 0
#> 28 24.00 0 67 1 0
#> 11.1 24.00 0 42 0 1
#> 28.1 24.00 0 67 1 0
#> 54 24.00 0 53 1 0
#> 67 24.00 0 25 0 0
#> 200.1 24.00 0 64 0 0
#> 44 24.00 0 56 0 0
#> 137 24.00 0 45 1 0
#> 75 24.00 0 21 1 0
#> 27 24.00 0 63 1 0
#> 200.2 24.00 0 64 0 0
#> 182 24.00 0 35 0 0
#> 152 24.00 0 36 0 1
#> 31.1 24.00 0 36 0 1
#> 178.1 24.00 0 52 1 0
#> 186.2 24.00 0 45 1 0
#> 118 24.00 0 44 1 0
#> 62.2 24.00 0 71 0 0
#> 198 24.00 0 66 0 1
#> 9 24.00 0 31 1 0
#> 17 24.00 0 38 0 1
#> 120 24.00 0 68 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.653 NA NA NA
#> 2 age, Cure model 0.0101 NA NA NA
#> 3 grade_ii, Cure model 0.384 NA NA NA
#> 4 grade_iii, Cure model 0.988 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00660 NA NA NA
#> 2 grade_ii, Survival model 0.505 NA NA NA
#> 3 grade_iii, Survival model 0.113 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.65330 0.01008 0.38387 0.98750
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 262.5
#> Residual Deviance: 253.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.6532963 0.0100777 0.3838736 0.9875037
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.006596554 0.504681838 0.112986752
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.558079351 0.729878355 0.240600795 0.097824631 0.013575164 0.013575164
#> [7] 0.606886107 0.885824509 0.927852231 0.072409401 0.312593384 0.285381185
#> [13] 0.885824509 0.948615910 0.388390741 0.231764397 0.350452384 0.240600795
#> [19] 0.917326611 0.802183932 0.558079351 0.627078722 0.049119077 0.331302859
#> [25] 0.398137208 0.340830219 0.026104911 0.467885744 0.258223853 0.164174329
#> [31] 0.647413189 0.360003167 0.760750942 0.927852231 0.417773621 0.822971133
#> [37] 0.989619371 0.558079351 0.517538844 0.843864384 0.948615910 0.791790252
#> [43] 0.740193923 0.948615910 0.072409401 0.517538844 0.447722263 0.478020405
#> [49] 0.360003167 0.001954865 0.223003796 0.131180618 0.276179085 0.172605232
#> [55] 0.147949976 0.007065372 0.360003167 0.558079351 0.657677691 0.026104911
#> [61] 0.698762776 0.214296898 0.822971133 0.457787825 0.843864384 0.172605232
#> [67] 0.285381185 0.478020405 0.507486065 0.771083467 0.312593384 0.558079351
#> [73] 0.285381185 0.547904769 0.906760692 0.537702751 0.398137208 0.979266566
#> [79] 0.437611488 0.417773621 0.750444961 0.197067136 0.064172341 0.114684966
#> [85] 0.709175856 0.678153039 0.088918565 0.114684966 0.627078722 0.147949976
#> [91] 0.657677691 0.258223853 0.172605232 0.131180618 0.719544911 0.771083467
#> [97] 0.049119077 0.205684998 0.606886107 0.802183932 0.864864500 0.478020405
#> [103] 0.864864500 0.678153039 0.097824631 0.041063677 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 29 140 76 197 86 86.1 157 101 70 15 88 8 101.1
#> 15.45 12.68 19.22 21.60 23.81 23.81 15.10 9.97 7.38 22.68 18.37 18.43 9.97
#> 25 111 58 41 76.1 149 43 29.1 180 69 108 30 51
#> 6.32 17.45 19.34 18.02 19.22 8.37 12.10 15.45 14.82 23.23 18.29 17.43 18.23
#> 164 181 97 68 96 184 42 70.1 45 10 127 29.2 100
#> 23.60 16.46 19.14 20.62 14.54 17.77 12.43 7.38 17.42 10.53 3.53 15.45 16.07
#> 52 25.1 49 154 25.2 15.1 100.1 106 192 184.1 24 170 99
#> 10.42 6.32 12.19 12.63 6.32 22.68 16.07 16.67 16.44 17.77 23.89 19.54 21.19
#> 179 128 32 78 184.2 29.3 57 164.1 81 166 10.1 171 52.1
#> 18.63 20.35 20.90 23.88 17.77 15.45 14.46 23.60 14.06 19.98 10.53 16.57 10.42
#> 128.1 8.1 85 188 56 88.1 29.4 8.2 167 16 39 30.1 91
#> 20.35 18.43 16.44 16.16 12.21 18.37 15.45 18.43 15.55 8.71 15.59 17.43 5.33
#> 23 45.1 177 150 113 153 60 13 169 153.1 180.1 32.1 57.1
#> 16.92 17.42 12.53 20.33 22.86 21.33 13.15 14.34 22.41 21.33 14.82 20.90 14.46
#> 97.1 128.2 99.1 123 56.1 69.1 158 157.1 43.1 145 192.1 145.1 13.1
#> 19.14 20.35 21.19 13.00 12.21 23.23 20.14 15.10 12.10 10.07 16.44 10.07 14.34
#> 197.1 129 126 95 193 64 31 2 87 47 2.1 138 141
#> 21.60 23.41 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148 178 21 71 142 62 132 98 94 80 82 173 122
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186 83 53 185 33 200 165 126.1 21.1 2.2 143 144 161
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 104 53.1 163 172 11 48 172.1 122.1 196 98.1 12 116 141.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186.1 62.1 82.1 132.1 21.2 3 112 122.2 147 163.1 82.2 173.1 20
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28 11.1 28.1 54 67 200.1 44 137 75 27 200.2 182 152
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31.1 178.1 186.2 118 62.2 198 9 17 120
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[83]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01753056 0.90741521 0.12471395
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.49736276 0.01291546 -0.40033090
#> grade_iii, Cure model
#> 1.08908441
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 39 15.59 1 37 0 1
#> 123 13.00 1 44 1 0
#> 6 15.64 1 39 0 0
#> 150 20.33 1 48 0 0
#> 190 20.81 1 42 1 0
#> 133 14.65 1 57 0 0
#> 61 10.12 1 36 0 1
#> 113 22.86 1 34 0 0
#> 149 8.37 1 33 1 0
#> 167 15.55 1 56 1 0
#> 181 16.46 1 45 0 1
#> 187 9.92 1 39 1 0
#> 184 17.77 1 38 0 0
#> 97 19.14 1 65 0 1
#> 168 23.72 1 70 0 0
#> 76 19.22 1 54 0 1
#> 79 16.23 1 54 1 0
#> 96 14.54 1 33 0 1
#> 4 17.64 1 NA 0 1
#> 105 19.75 1 60 0 0
#> 134 17.81 1 47 1 0
#> 41 18.02 1 40 1 0
#> 25 6.32 1 34 1 0
#> 68 20.62 1 44 0 0
#> 180 14.82 1 37 0 0
#> 6.1 15.64 1 39 0 0
#> 92 22.92 1 47 0 1
#> 42 12.43 1 49 0 1
#> 130 16.47 1 53 0 1
#> 195 11.76 1 NA 1 0
#> 188 16.16 1 46 0 1
#> 23 16.92 1 61 0 0
#> 49 12.19 1 48 1 0
#> 88 18.37 1 47 0 0
#> 60 13.15 1 38 1 0
#> 10 10.53 1 34 0 0
#> 79.1 16.23 1 54 1 0
#> 16 8.71 1 71 0 1
#> 130.1 16.47 1 53 0 1
#> 97.1 19.14 1 65 0 1
#> 15 22.68 1 48 0 0
#> 149.1 8.37 1 33 1 0
#> 99 21.19 1 38 0 1
#> 68.1 20.62 1 44 0 0
#> 114 13.68 1 NA 0 0
#> 23.1 16.92 1 61 0 0
#> 166 19.98 1 48 0 0
#> 167.1 15.55 1 56 1 0
#> 197 21.60 1 69 1 0
#> 26 15.77 1 49 0 1
#> 57 14.46 1 45 0 1
#> 114.1 13.68 1 NA 0 0
#> 111 17.45 1 47 0 1
#> 106 16.67 1 49 1 0
#> 70 7.38 1 30 1 0
#> 81 14.06 1 34 0 0
#> 155 13.08 1 26 0 0
#> 25.1 6.32 1 34 1 0
#> 92.1 22.92 1 47 0 1
#> 158 20.14 1 74 1 0
#> 14 12.89 1 21 0 0
#> 55 19.34 1 69 0 1
#> 139 21.49 1 63 1 0
#> 6.2 15.64 1 39 0 0
#> 168.1 23.72 1 70 0 0
#> 29 15.45 1 68 1 0
#> 183 9.24 1 67 1 0
#> 110 17.56 1 65 0 1
#> 26.1 15.77 1 49 0 1
#> 66 22.13 1 53 0 0
#> 99.1 21.19 1 38 0 1
#> 175 21.91 1 43 0 0
#> 136 21.83 1 43 0 1
#> 188.1 16.16 1 46 0 1
#> 42.1 12.43 1 49 0 1
#> 91 5.33 1 61 0 1
#> 192 16.44 1 31 1 0
#> 158.1 20.14 1 74 1 0
#> 125 15.65 1 67 1 0
#> 128 20.35 1 35 0 1
#> 187.1 9.92 1 39 1 0
#> 90 20.94 1 50 0 1
#> 18 15.21 1 49 1 0
#> 154 12.63 1 20 1 0
#> 32 20.90 1 37 1 0
#> 171 16.57 1 41 0 1
#> 30 17.43 1 78 0 0
#> 18.1 15.21 1 49 1 0
#> 169 22.41 1 46 0 0
#> 145 10.07 1 65 1 0
#> 92.2 22.92 1 47 0 1
#> 157 15.10 1 47 0 0
#> 157.1 15.10 1 47 0 0
#> 171.1 16.57 1 41 0 1
#> 167.2 15.55 1 56 1 0
#> 177 12.53 1 75 0 0
#> 6.3 15.64 1 39 0 0
#> 105.1 19.75 1 60 0 0
#> 26.2 15.77 1 49 0 1
#> 77 7.27 1 67 0 1
#> 150.1 20.33 1 48 0 0
#> 111.1 17.45 1 47 0 1
#> 110.1 17.56 1 65 0 1
#> 188.2 16.16 1 46 0 1
#> 108 18.29 1 39 0 1
#> 69 23.23 1 25 0 1
#> 199 19.81 1 NA 0 1
#> 168.2 23.72 1 70 0 0
#> 60.1 13.15 1 38 1 0
#> 194 22.40 1 38 0 1
#> 110.2 17.56 1 65 0 1
#> 166.1 19.98 1 48 0 0
#> 34 24.00 0 36 0 0
#> 44 24.00 0 56 0 0
#> 7 24.00 0 37 1 0
#> 73 24.00 0 NA 0 1
#> 147 24.00 0 76 1 0
#> 178 24.00 0 52 1 0
#> 87 24.00 0 27 0 0
#> 186 24.00 0 45 1 0
#> 34.1 24.00 0 36 0 0
#> 46 24.00 0 71 0 0
#> 176 24.00 0 43 0 1
#> 64 24.00 0 43 0 0
#> 11 24.00 0 42 0 1
#> 48 24.00 0 31 1 0
#> 178.1 24.00 0 52 1 0
#> 152 24.00 0 36 0 1
#> 185 24.00 0 44 1 0
#> 73.1 24.00 0 NA 0 1
#> 148 24.00 0 61 1 0
#> 141 24.00 0 44 1 0
#> 143 24.00 0 51 0 0
#> 75 24.00 0 21 1 0
#> 98 24.00 0 34 1 0
#> 174 24.00 0 49 1 0
#> 178.2 24.00 0 52 1 0
#> 176.1 24.00 0 43 0 1
#> 185.1 24.00 0 44 1 0
#> 165 24.00 0 47 0 0
#> 142 24.00 0 53 0 0
#> 121 24.00 0 57 1 0
#> 196 24.00 0 19 0 0
#> 19 24.00 0 57 0 1
#> 160 24.00 0 31 1 0
#> 9 24.00 0 31 1 0
#> 7.1 24.00 0 37 1 0
#> 3 24.00 0 31 1 0
#> 196.1 24.00 0 19 0 0
#> 54 24.00 0 53 1 0
#> 121.1 24.00 0 57 1 0
#> 174.1 24.00 0 49 1 0
#> 162 24.00 0 51 0 0
#> 53 24.00 0 32 0 1
#> 135 24.00 0 58 1 0
#> 120 24.00 0 68 0 1
#> 9.1 24.00 0 31 1 0
#> 135.1 24.00 0 58 1 0
#> 12 24.00 0 63 0 0
#> 148.1 24.00 0 61 1 0
#> 65 24.00 0 57 1 0
#> 74 24.00 0 43 0 1
#> 200 24.00 0 64 0 0
#> 121.2 24.00 0 57 1 0
#> 87.1 24.00 0 27 0 0
#> 84 24.00 0 39 0 1
#> 17 24.00 0 38 0 1
#> 33 24.00 0 53 0 0
#> 62 24.00 0 71 0 0
#> 148.2 24.00 0 61 1 0
#> 38 24.00 0 31 1 0
#> 163 24.00 0 66 0 0
#> 146 24.00 0 63 1 0
#> 34.2 24.00 0 36 0 0
#> 62.1 24.00 0 71 0 0
#> 200.1 24.00 0 64 0 0
#> 112 24.00 0 61 0 0
#> 22 24.00 0 52 1 0
#> 38.1 24.00 0 31 1 0
#> 161 24.00 0 45 0 0
#> 138 24.00 0 44 1 0
#> 44.1 24.00 0 56 0 0
#> 38.2 24.00 0 31 1 0
#> 28 24.00 0 67 1 0
#> 71 24.00 0 51 0 0
#> 7.2 24.00 0 37 1 0
#> 54.1 24.00 0 53 1 0
#> 143.1 24.00 0 51 0 0
#> 104 24.00 0 50 1 0
#> 20 24.00 0 46 1 0
#> 196.2 24.00 0 19 0 0
#> 172 24.00 0 41 0 0
#> 84.1 24.00 0 39 0 1
#> 38.3 24.00 0 31 1 0
#> 80 24.00 0 41 0 0
#> 20.1 24.00 0 46 1 0
#> 109 24.00 0 48 0 0
#> 94 24.00 0 51 0 1
#> 185.2 24.00 0 44 1 0
#> 160.1 24.00 0 31 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.497 NA NA NA
#> 2 age, Cure model 0.0129 NA NA NA
#> 3 grade_ii, Cure model -0.400 NA NA NA
#> 4 grade_iii, Cure model 1.09 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0175 NA NA NA
#> 2 grade_ii, Survival model 0.907 NA NA NA
#> 3 grade_iii, Survival model 0.125 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.49736 0.01292 -0.40033 1.08908
#>
#> Degrees of Freedom: 192 Total (i.e. Null); 189 Residual
#> Null Deviance: 265.3
#> Residual Deviance: 248.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.49736276 0.01291546 -0.40033090 1.08908441
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01753056 0.90741521 0.12471395
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 4.869620e-01 7.077939e-01 4.389497e-01 7.437931e-02 5.469372e-02
#> [6] 6.133404e-01 8.177454e-01 6.630955e-03 9.022120e-01 4.995680e-01
#> [11] 3.168069e-01 8.460189e-01 1.838700e-01 1.364231e-01 4.468503e-05
#> [16] 1.291608e-01 3.385469e-01 6.266640e-01 1.089341e-01 1.758183e-01
#> [21] 1.677343e-01 9.582148e-01 5.937054e-02 6.001972e-01 4.389497e-01
#> [26] 2.520271e-03 7.622210e-01 2.956360e-01 3.598365e-01 2.454991e-01
#> [31] 7.898227e-01 1.515617e-01 6.673510e-01 8.037296e-01 3.385469e-01
#> [36] 8.879665e-01 2.956360e-01 1.364231e-01 8.719490e-03 9.022120e-01
#> [41] 3.627886e-02 5.937054e-02 2.454991e-01 9.671104e-02 4.995680e-01
#> [46] 2.792111e-02 3.927153e-01 6.400917e-01 2.177503e-01 2.652327e-01
#> [51] 9.301373e-01 6.536576e-01 6.941601e-01 9.582148e-01 2.520271e-03
#> [56] 8.530866e-02 7.213896e-01 1.221205e-01 3.205096e-02 4.389497e-01
#> [61] 4.468503e-05 5.366366e-01 8.738734e-01 1.920971e-01 3.927153e-01
#> [66] 1.689243e-02 3.627886e-02 2.025638e-02 2.394540e-02 3.598365e-01
#> [71] 7.622210e-01 9.859246e-01 3.277560e-01 8.530866e-02 4.270921e-01
#> [76] 6.915311e-02 8.460189e-01 4.505206e-02 5.493632e-01 7.350646e-01
#> [81] 4.994137e-02 2.752713e-01 2.359412e-01 5.493632e-01 1.113915e-02
#> [86] 8.318572e-01 2.520271e-03 5.744646e-01 5.744646e-01 2.752713e-01
#> [91] 4.995680e-01 7.485527e-01 4.389497e-01 1.089341e-01 3.927153e-01
#> [96] 9.441082e-01 7.437931e-02 2.177503e-01 1.920971e-01 3.598365e-01
#> [101] 1.595602e-01 1.354375e-03 4.468503e-05 6.673510e-01 1.389087e-02
#> [106] 1.920971e-01 9.671104e-02 0.000000e+00 0.000000e+00 0.000000e+00
#> [111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [186] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [191] 0.000000e+00 0.000000e+00 0.000000e+00
#>
#> $Time
#> 39 123 6 150 190 133 61 113 149 167 181 187 184
#> 15.59 13.00 15.64 20.33 20.81 14.65 10.12 22.86 8.37 15.55 16.46 9.92 17.77
#> 97 168 76 79 96 105 134 41 25 68 180 6.1 92
#> 19.14 23.72 19.22 16.23 14.54 19.75 17.81 18.02 6.32 20.62 14.82 15.64 22.92
#> 42 130 188 23 49 88 60 10 79.1 16 130.1 97.1 15
#> 12.43 16.47 16.16 16.92 12.19 18.37 13.15 10.53 16.23 8.71 16.47 19.14 22.68
#> 149.1 99 68.1 23.1 166 167.1 197 26 57 111 106 70 81
#> 8.37 21.19 20.62 16.92 19.98 15.55 21.60 15.77 14.46 17.45 16.67 7.38 14.06
#> 155 25.1 92.1 158 14 55 139 6.2 168.1 29 183 110 26.1
#> 13.08 6.32 22.92 20.14 12.89 19.34 21.49 15.64 23.72 15.45 9.24 17.56 15.77
#> 66 99.1 175 136 188.1 42.1 91 192 158.1 125 128 187.1 90
#> 22.13 21.19 21.91 21.83 16.16 12.43 5.33 16.44 20.14 15.65 20.35 9.92 20.94
#> 18 154 32 171 30 18.1 169 145 92.2 157 157.1 171.1 167.2
#> 15.21 12.63 20.90 16.57 17.43 15.21 22.41 10.07 22.92 15.10 15.10 16.57 15.55
#> 177 6.3 105.1 26.2 77 150.1 111.1 110.1 188.2 108 69 168.2 60.1
#> 12.53 15.64 19.75 15.77 7.27 20.33 17.45 17.56 16.16 18.29 23.23 23.72 13.15
#> 194 110.2 166.1 34 44 7 147 178 87 186 34.1 46 176
#> 22.40 17.56 19.98 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64 11 48 178.1 152 185 148 141 143 75 98 174 178.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176.1 185.1 165 142 121 196 19 160 9 7.1 3 196.1 54
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 121.1 174.1 162 53 135 120 9.1 135.1 12 148.1 65 74 200
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 121.2 87.1 84 17 33 62 148.2 38 163 146 34.2 62.1 200.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 112 22 38.1 161 138 44.1 38.2 28 71 7.2 54.1 143.1 104
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20 196.2 172 84.1 38.3 80 20.1 109 94 185.2 160.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[84]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.007215037 0.614221043 0.321005863
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.84014251 0.02079323 -0.01587084
#> grade_iii, Cure model
#> 0.29392190
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 78 23.88 1 43 0 0
#> 154 12.63 1 20 1 0
#> 171 16.57 1 41 0 1
#> 60 13.15 1 38 1 0
#> 195 11.76 1 NA 1 0
#> 40 18.00 1 28 1 0
#> 169 22.41 1 46 0 0
#> 124 9.73 1 NA 1 0
#> 140 12.68 1 59 1 0
#> 10 10.53 1 34 0 0
#> 106 16.67 1 49 1 0
#> 167 15.55 1 56 1 0
#> 42 12.43 1 49 0 1
#> 6 15.64 1 39 0 0
#> 171.1 16.57 1 41 0 1
#> 183 9.24 1 67 1 0
#> 183.1 9.24 1 67 1 0
#> 52 10.42 1 52 0 1
#> 86 23.81 1 58 0 1
#> 128 20.35 1 35 0 1
#> 55 19.34 1 69 0 1
#> 18 15.21 1 49 1 0
#> 190 20.81 1 42 1 0
#> 164 23.60 1 76 0 1
#> 111 17.45 1 47 0 1
#> 13 14.34 1 54 0 1
#> 170 19.54 1 43 0 1
#> 81 14.06 1 34 0 0
#> 129 23.41 1 53 1 0
#> 125 15.65 1 67 1 0
#> 8 18.43 1 32 0 0
#> 107 11.18 1 54 1 0
#> 157 15.10 1 47 0 0
#> 180 14.82 1 37 0 0
#> 77 7.27 1 67 0 1
#> 52.1 10.42 1 52 0 1
#> 59 10.16 1 NA 1 0
#> 58 19.34 1 39 0 0
#> 188 16.16 1 46 0 1
#> 43 12.10 1 61 0 1
#> 158 20.14 1 74 1 0
#> 155 13.08 1 26 0 0
#> 93 10.33 1 52 0 1
#> 96 14.54 1 33 0 1
#> 197 21.60 1 69 1 0
#> 100 16.07 1 60 0 0
#> 180.1 14.82 1 37 0 0
#> 157.1 15.10 1 47 0 0
#> 190.1 20.81 1 42 1 0
#> 134 17.81 1 47 1 0
#> 164.1 23.60 1 76 0 1
#> 190.2 20.81 1 42 1 0
#> 128.1 20.35 1 35 0 1
#> 183.2 9.24 1 67 1 0
#> 133 14.65 1 57 0 0
#> 179 18.63 1 42 0 0
#> 108 18.29 1 39 0 1
#> 106.1 16.67 1 49 1 0
#> 189 10.51 1 NA 1 0
#> 169.1 22.41 1 46 0 0
#> 42.1 12.43 1 49 0 1
#> 106.2 16.67 1 49 1 0
#> 77.1 7.27 1 67 0 1
#> 183.3 9.24 1 67 1 0
#> 68 20.62 1 44 0 0
#> 149 8.37 1 33 1 0
#> 25 6.32 1 34 1 0
#> 39 15.59 1 37 0 1
#> 13.1 14.34 1 54 0 1
#> 167.1 15.55 1 56 1 0
#> 192 16.44 1 31 1 0
#> 188.1 16.16 1 46 0 1
#> 105 19.75 1 60 0 0
#> 68.1 20.62 1 44 0 0
#> 164.2 23.60 1 76 0 1
#> 158.1 20.14 1 74 1 0
#> 50 10.02 1 NA 1 0
#> 79 16.23 1 54 1 0
#> 78.1 23.88 1 43 0 0
#> 114 13.68 1 NA 0 0
#> 69 23.23 1 25 0 1
#> 168 23.72 1 70 0 0
#> 5 16.43 1 51 0 1
#> 56 12.21 1 60 0 0
#> 69.1 23.23 1 25 0 1
#> 36 21.19 1 48 0 1
#> 139 21.49 1 63 1 0
#> 86.1 23.81 1 58 0 1
#> 96.1 14.54 1 33 0 1
#> 29 15.45 1 68 1 0
#> 177 12.53 1 75 0 0
#> 180.2 14.82 1 37 0 0
#> 170.1 19.54 1 43 0 1
#> 93.1 10.33 1 52 0 1
#> 128.2 20.35 1 35 0 1
#> 78.2 23.88 1 43 0 0
#> 91 5.33 1 61 0 1
#> 179.1 18.63 1 42 0 0
#> 39.1 15.59 1 37 0 1
#> 157.2 15.10 1 47 0 0
#> 155.1 13.08 1 26 0 0
#> 49 12.19 1 48 1 0
#> 108.1 18.29 1 39 0 1
#> 134.1 17.81 1 47 1 0
#> 158.2 20.14 1 74 1 0
#> 140.1 12.68 1 59 1 0
#> 58.1 19.34 1 39 0 0
#> 8.1 18.43 1 32 0 0
#> 181 16.46 1 45 0 1
#> 24 23.89 1 38 0 0
#> 158.3 20.14 1 74 1 0
#> 179.2 18.63 1 42 0 0
#> 116 24.00 0 58 0 1
#> 146 24.00 0 63 1 0
#> 138 24.00 0 44 1 0
#> 34 24.00 0 36 0 0
#> 122 24.00 0 66 0 0
#> 122.1 24.00 0 66 0 0
#> 182 24.00 0 35 0 0
#> 122.2 24.00 0 66 0 0
#> 73 24.00 0 NA 0 1
#> 80 24.00 0 41 0 0
#> 2 24.00 0 9 0 0
#> 172 24.00 0 41 0 0
#> 2.1 24.00 0 9 0 0
#> 48 24.00 0 31 1 0
#> 75 24.00 0 21 1 0
#> 173 24.00 0 19 0 1
#> 138.1 24.00 0 44 1 0
#> 193 24.00 0 45 0 1
#> 67 24.00 0 25 0 0
#> 141 24.00 0 44 1 0
#> 95 24.00 0 68 0 1
#> 135 24.00 0 58 1 0
#> 182.1 24.00 0 35 0 0
#> 65 24.00 0 57 1 0
#> 144 24.00 0 28 0 1
#> 176 24.00 0 43 0 1
#> 118 24.00 0 44 1 0
#> 74 24.00 0 43 0 1
#> 137 24.00 0 45 1 0
#> 122.3 24.00 0 66 0 0
#> 165 24.00 0 47 0 0
#> 20 24.00 0 46 1 0
#> 115 24.00 0 NA 1 0
#> 112 24.00 0 61 0 0
#> 176.1 24.00 0 43 0 1
#> 148 24.00 0 61 1 0
#> 48.1 24.00 0 31 1 0
#> 44 24.00 0 56 0 0
#> 11 24.00 0 42 0 1
#> 94 24.00 0 51 0 1
#> 104 24.00 0 50 1 0
#> 74.1 24.00 0 43 0 1
#> 35 24.00 0 51 0 0
#> 176.2 24.00 0 43 0 1
#> 54 24.00 0 53 1 0
#> 135.1 24.00 0 58 1 0
#> 135.2 24.00 0 58 1 0
#> 35.1 24.00 0 51 0 0
#> 141.1 24.00 0 44 1 0
#> 147 24.00 0 76 1 0
#> 115.1 24.00 0 NA 1 0
#> 83 24.00 0 6 0 0
#> 83.1 24.00 0 6 0 0
#> 28 24.00 0 67 1 0
#> 54.1 24.00 0 53 1 0
#> 71 24.00 0 51 0 0
#> 119 24.00 0 17 0 0
#> 116.1 24.00 0 58 0 1
#> 11.1 24.00 0 42 0 1
#> 116.2 24.00 0 58 0 1
#> 20.1 24.00 0 46 1 0
#> 28.1 24.00 0 67 1 0
#> 65.1 24.00 0 57 1 0
#> 94.1 24.00 0 51 0 1
#> 141.2 24.00 0 44 1 0
#> 82 24.00 0 34 0 0
#> 144.1 24.00 0 28 0 1
#> 116.3 24.00 0 58 0 1
#> 17 24.00 0 38 0 1
#> 31 24.00 0 36 0 1
#> 120 24.00 0 68 0 1
#> 82.1 24.00 0 34 0 0
#> 196 24.00 0 19 0 0
#> 138.2 24.00 0 44 1 0
#> 84 24.00 0 39 0 1
#> 83.2 24.00 0 6 0 0
#> 87 24.00 0 27 0 0
#> 82.2 24.00 0 34 0 0
#> 54.2 24.00 0 53 1 0
#> 22 24.00 0 52 1 0
#> 72 24.00 0 40 0 1
#> 198 24.00 0 66 0 1
#> 80.1 24.00 0 41 0 0
#> 46 24.00 0 71 0 0
#> 191 24.00 0 60 0 1
#> 83.3 24.00 0 6 0 0
#> 34.1 24.00 0 36 0 0
#> 87.1 24.00 0 27 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.840 NA NA NA
#> 2 age, Cure model 0.0208 NA NA NA
#> 3 grade_ii, Cure model -0.0159 NA NA NA
#> 4 grade_iii, Cure model 0.294 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00722 NA NA NA
#> 2 grade_ii, Survival model 0.614 NA NA NA
#> 3 grade_iii, Survival model 0.321 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.84014 0.02079 -0.01587 0.29392
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 262.5
#> Residual Deviance: 256.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.84014251 0.02079323 -0.01587084 0.29392190
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.007215037 0.614221043 0.321005863
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.012010473 0.792185279 0.472023342 0.744708965 0.405205804 0.118824099
#> [7] 0.773260428 0.868102535 0.444022113 0.594329723 0.811135069 0.566123359
#> [13] 0.472023342 0.915547656 0.915547656 0.877619981 0.033092033 0.216310282
#> [19] 0.308407651 0.622288438 0.169874206 0.060591635 0.434298607 0.716148153
#> [25] 0.289611630 0.735129263 0.089154582 0.556696715 0.365676852 0.858607735
#> [31] 0.631601556 0.659480572 0.962322455 0.877619981 0.308407651 0.528624867
#> [37] 0.849086421 0.244124052 0.754239017 0.896573235 0.697200369 0.138977743
#> [43] 0.547247713 0.659480572 0.631601556 0.169874206 0.415076943 0.060591635
#> [49] 0.169874206 0.216310282 0.915547656 0.687638618 0.336723457 0.385461691
#> [55] 0.444022113 0.118824099 0.811135069 0.444022113 0.962322455 0.915547656
#> [61] 0.197171039 0.952889432 0.981151107 0.575588662 0.716148153 0.594329723
#> [67] 0.500373165 0.528624867 0.280049373 0.197171039 0.060591635 0.244124052
#> [73] 0.519233608 0.012010473 0.099596891 0.050310063 0.509799383 0.830034540
#> [79] 0.099596891 0.159605234 0.149352973 0.033092033 0.697200369 0.612933628
#> [85] 0.801636773 0.659480572 0.289611630 0.896573235 0.216310282 0.012010473
#> [91] 0.990570519 0.336723457 0.575588662 0.631601556 0.754239017 0.839577082
#> [97] 0.385461691 0.415076943 0.244124052 0.773260428 0.308407651 0.365676852
#> [103] 0.490861339 0.003223084 0.244124052 0.336723457 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 78 154 171 60 40 169 140 10 106 167 42 6 171.1
#> 23.88 12.63 16.57 13.15 18.00 22.41 12.68 10.53 16.67 15.55 12.43 15.64 16.57
#> 183 183.1 52 86 128 55 18 190 164 111 13 170 81
#> 9.24 9.24 10.42 23.81 20.35 19.34 15.21 20.81 23.60 17.45 14.34 19.54 14.06
#> 129 125 8 107 157 180 77 52.1 58 188 43 158 155
#> 23.41 15.65 18.43 11.18 15.10 14.82 7.27 10.42 19.34 16.16 12.10 20.14 13.08
#> 93 96 197 100 180.1 157.1 190.1 134 164.1 190.2 128.1 183.2 133
#> 10.33 14.54 21.60 16.07 14.82 15.10 20.81 17.81 23.60 20.81 20.35 9.24 14.65
#> 179 108 106.1 169.1 42.1 106.2 77.1 183.3 68 149 25 39 13.1
#> 18.63 18.29 16.67 22.41 12.43 16.67 7.27 9.24 20.62 8.37 6.32 15.59 14.34
#> 167.1 192 188.1 105 68.1 164.2 158.1 79 78.1 69 168 5 56
#> 15.55 16.44 16.16 19.75 20.62 23.60 20.14 16.23 23.88 23.23 23.72 16.43 12.21
#> 69.1 36 139 86.1 96.1 29 177 180.2 170.1 93.1 128.2 78.2 91
#> 23.23 21.19 21.49 23.81 14.54 15.45 12.53 14.82 19.54 10.33 20.35 23.88 5.33
#> 179.1 39.1 157.2 155.1 49 108.1 134.1 158.2 140.1 58.1 8.1 181 24
#> 18.63 15.59 15.10 13.08 12.19 18.29 17.81 20.14 12.68 19.34 18.43 16.46 23.89
#> 158.3 179.2 116 146 138 34 122 122.1 182 122.2 80 2 172
#> 20.14 18.63 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 2.1 48 75 173 138.1 193 67 141 95 135 182.1 65 144
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176 118 74 137 122.3 165 20 112 176.1 148 48.1 44 11
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94 104 74.1 35 176.2 54 135.1 135.2 35.1 141.1 147 83 83.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28 54.1 71 119 116.1 11.1 116.2 20.1 28.1 65.1 94.1 141.2 82
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 144.1 116.3 17 31 120 82.1 196 138.2 84 83.2 87 82.2 54.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 22 72 198 80.1 46 191 83.3 34.1 87.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[85]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.006220031 0.744513715 0.221466101
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.02937457 0.01167812 0.70174085
#> grade_iii, Cure model
#> 1.29839641
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 66 22.13 1 53 0 0
#> 168 23.72 1 70 0 0
#> 5 16.43 1 51 0 1
#> 187 9.92 1 39 1 0
#> 81 14.06 1 34 0 0
#> 154 12.63 1 20 1 0
#> 194 22.40 1 38 0 1
#> 49 12.19 1 48 1 0
#> 199 19.81 1 NA 0 1
#> 177 12.53 1 75 0 0
#> 79 16.23 1 54 1 0
#> 29 15.45 1 68 1 0
#> 37 12.52 1 57 1 0
#> 13 14.34 1 54 0 1
#> 39 15.59 1 37 0 1
#> 134 17.81 1 47 1 0
#> 139 21.49 1 63 1 0
#> 199.1 19.81 1 NA 0 1
#> 130 16.47 1 53 0 1
#> 85 16.44 1 36 0 0
#> 125 15.65 1 67 1 0
#> 97 19.14 1 65 0 1
#> 52 10.42 1 52 0 1
#> 39.1 15.59 1 37 0 1
#> 76 19.22 1 54 0 1
#> 179 18.63 1 42 0 0
#> 50 10.02 1 NA 1 0
#> 23 16.92 1 61 0 0
#> 114 13.68 1 NA 0 0
#> 36 21.19 1 48 0 1
#> 40 18.00 1 28 1 0
#> 37.1 12.52 1 57 1 0
#> 97.1 19.14 1 65 0 1
#> 164 23.60 1 76 0 1
#> 14 12.89 1 21 0 0
#> 110 17.56 1 65 0 1
#> 136 21.83 1 43 0 1
#> 25 6.32 1 34 1 0
#> 189 10.51 1 NA 1 0
#> 188 16.16 1 46 0 1
#> 37.2 12.52 1 57 1 0
#> 123 13.00 1 44 1 0
#> 107 11.18 1 54 1 0
#> 96 14.54 1 33 0 1
#> 5.1 16.43 1 51 0 1
#> 189.1 10.51 1 NA 1 0
#> 106 16.67 1 49 1 0
#> 5.2 16.43 1 51 0 1
#> 26 15.77 1 49 0 1
#> 190 20.81 1 42 1 0
#> 6 15.64 1 39 0 0
#> 197 21.60 1 69 1 0
#> 39.2 15.59 1 37 0 1
#> 39.3 15.59 1 37 0 1
#> 130.1 16.47 1 53 0 1
#> 49.1 12.19 1 48 1 0
#> 79.1 16.23 1 54 1 0
#> 55 19.34 1 69 0 1
#> 45 17.42 1 54 0 1
#> 32 20.90 1 37 1 0
#> 63 22.77 1 31 1 0
#> 155 13.08 1 26 0 0
#> 39.4 15.59 1 37 0 1
#> 164.1 23.60 1 76 0 1
#> 190.1 20.81 1 42 1 0
#> 14.1 12.89 1 21 0 0
#> 190.2 20.81 1 42 1 0
#> 24 23.89 1 38 0 0
#> 90 20.94 1 50 0 1
#> 123.1 13.00 1 44 1 0
#> 124 9.73 1 NA 1 0
#> 99 21.19 1 38 0 1
#> 18 15.21 1 49 1 0
#> 189.2 10.51 1 NA 1 0
#> 164.2 23.60 1 76 0 1
#> 69 23.23 1 25 0 1
#> 29.1 15.45 1 68 1 0
#> 106.1 16.67 1 49 1 0
#> 30 17.43 1 78 0 0
#> 166 19.98 1 48 0 0
#> 49.2 12.19 1 48 1 0
#> 177.1 12.53 1 75 0 0
#> 81.1 14.06 1 34 0 0
#> 183 9.24 1 67 1 0
#> 55.1 19.34 1 69 0 1
#> 23.1 16.92 1 61 0 0
#> 171 16.57 1 41 0 1
#> 36.1 21.19 1 48 0 1
#> 113 22.86 1 34 0 0
#> 85.1 16.44 1 36 0 0
#> 16 8.71 1 71 0 1
#> 154.1 12.63 1 20 1 0
#> 66.1 22.13 1 53 0 0
#> 101 9.97 1 10 0 1
#> 90.1 20.94 1 50 0 1
#> 105 19.75 1 60 0 0
#> 43 12.10 1 61 0 1
#> 114.1 13.68 1 NA 0 0
#> 130.2 16.47 1 53 0 1
#> 93 10.33 1 52 0 1
#> 69.1 23.23 1 25 0 1
#> 24.1 23.89 1 38 0 0
#> 79.2 16.23 1 54 1 0
#> 101.1 9.97 1 10 0 1
#> 55.2 19.34 1 69 0 1
#> 167 15.55 1 56 1 0
#> 139.1 21.49 1 63 1 0
#> 128 20.35 1 35 0 1
#> 194.1 22.40 1 38 0 1
#> 106.2 16.67 1 49 1 0
#> 127 3.53 1 62 0 1
#> 86 23.81 1 58 0 1
#> 173 24.00 0 19 0 1
#> 165 24.00 0 47 0 0
#> 64 24.00 0 43 0 0
#> 21 24.00 0 47 0 0
#> 115 24.00 0 NA 1 0
#> 80 24.00 0 41 0 0
#> 120 24.00 0 68 0 1
#> 172 24.00 0 41 0 0
#> 141 24.00 0 44 1 0
#> 141.1 24.00 0 44 1 0
#> 186 24.00 0 45 1 0
#> 20 24.00 0 46 1 0
#> 185 24.00 0 44 1 0
#> 75 24.00 0 21 1 0
#> 144 24.00 0 28 0 1
#> 160 24.00 0 31 1 0
#> 98 24.00 0 34 1 0
#> 116 24.00 0 58 0 1
#> 33 24.00 0 53 0 0
#> 182 24.00 0 35 0 0
#> 34 24.00 0 36 0 0
#> 132 24.00 0 55 0 0
#> 137 24.00 0 45 1 0
#> 34.1 24.00 0 36 0 0
#> 147 24.00 0 76 1 0
#> 173.1 24.00 0 19 0 1
#> 34.2 24.00 0 36 0 0
#> 165.1 24.00 0 47 0 0
#> 21.1 24.00 0 47 0 0
#> 151 24.00 0 42 0 0
#> 46 24.00 0 71 0 0
#> 115.1 24.00 0 NA 1 0
#> 11 24.00 0 42 0 1
#> 103 24.00 0 56 1 0
#> 9 24.00 0 31 1 0
#> 34.3 24.00 0 36 0 0
#> 163 24.00 0 66 0 0
#> 38 24.00 0 31 1 0
#> 118 24.00 0 44 1 0
#> 95 24.00 0 68 0 1
#> 35 24.00 0 51 0 0
#> 115.2 24.00 0 NA 1 0
#> 12 24.00 0 63 0 0
#> 122 24.00 0 66 0 0
#> 198 24.00 0 66 0 1
#> 9.1 24.00 0 31 1 0
#> 172.1 24.00 0 41 0 0
#> 2 24.00 0 9 0 0
#> 144.1 24.00 0 28 0 1
#> 103.1 24.00 0 56 1 0
#> 17 24.00 0 38 0 1
#> 12.1 24.00 0 63 0 0
#> 75.1 24.00 0 21 1 0
#> 191 24.00 0 60 0 1
#> 19 24.00 0 57 0 1
#> 28 24.00 0 67 1 0
#> 83 24.00 0 6 0 0
#> 185.1 24.00 0 44 1 0
#> 73 24.00 0 NA 0 1
#> 122.1 24.00 0 66 0 0
#> 116.1 24.00 0 58 0 1
#> 33.1 24.00 0 53 0 0
#> 116.2 24.00 0 58 0 1
#> 22 24.00 0 52 1 0
#> 27 24.00 0 63 1 0
#> 126 24.00 0 48 0 0
#> 135 24.00 0 58 1 0
#> 174 24.00 0 49 1 0
#> 182.1 24.00 0 35 0 0
#> 122.2 24.00 0 66 0 0
#> 147.1 24.00 0 76 1 0
#> 198.1 24.00 0 66 0 1
#> 1 24.00 0 23 1 0
#> 95.1 24.00 0 68 0 1
#> 182.2 24.00 0 35 0 0
#> 151.1 24.00 0 42 0 0
#> 75.2 24.00 0 21 1 0
#> 84 24.00 0 39 0 1
#> 2.1 24.00 0 9 0 0
#> 152 24.00 0 36 0 1
#> 17.1 24.00 0 38 0 1
#> 17.2 24.00 0 38 0 1
#> 34.4 24.00 0 36 0 0
#> 165.2 24.00 0 47 0 0
#> 34.5 24.00 0 36 0 0
#> 104 24.00 0 50 1 0
#> 112 24.00 0 61 0 0
#> 135.1 24.00 0 58 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.03 NA NA NA
#> 2 age, Cure model 0.0117 NA NA NA
#> 3 grade_ii, Cure model 0.702 NA NA NA
#> 4 grade_iii, Cure model 1.30 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00622 NA NA NA
#> 2 grade_ii, Survival model 0.745 NA NA NA
#> 3 grade_iii, Survival model 0.221 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.02937 0.01168 0.70174 1.29840
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 257.3
#> Residual Deviance: 243.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.02937457 0.01167812 0.70174085 1.29839641
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.006220031 0.744513715 0.221466101
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.138153997 0.030103483 0.547621825 0.955987506 0.747095929 0.812444676
#> [7] 0.117076901 0.876055535 0.830673378 0.576804122 0.700137188 0.849052451
#> [13] 0.737697425 0.643803290 0.401392320 0.182817380 0.499267207 0.528086113
#> [19] 0.624567564 0.361410719 0.920452647 0.643803290 0.351415826 0.381305649
#> [25] 0.440935147 0.203463730 0.391448026 0.849052451 0.361410719 0.041580938
#> [31] 0.793857718 0.411197747 0.160179698 0.982454365 0.605260180 0.849052451
#> [37] 0.775323913 0.911547852 0.728311849 0.547621825 0.460909557 0.547621825
#> [43] 0.614907813 0.265182454 0.634169716 0.171636690 0.643803290 0.643803290
#> [49] 0.499267207 0.876055535 0.576804122 0.322362698 0.430976365 0.254796596
#> [55] 0.106052325 0.765864169 0.643803290 0.041580938 0.265182454 0.793857718
#> [61] 0.265182454 0.005638809 0.233887107 0.775323913 0.203463730 0.718924299
#> [67] 0.041580938 0.072253842 0.700137188 0.460909557 0.421042410 0.302819912
#> [73] 0.876055535 0.830673378 0.747095929 0.964825395 0.322362698 0.440935147
#> [79] 0.489528854 0.203463730 0.094116414 0.528086113 0.973631995 0.812444676
#> [85] 0.138153997 0.938287255 0.233887107 0.312543721 0.902598931 0.499267207
#> [91] 0.929365804 0.072253842 0.005638809 0.576804122 0.938287255 0.322362698
#> [97] 0.690581868 0.182817380 0.293176054 0.117076901 0.460909557 0.991221304
#> [103] 0.020011449 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000
#>
#> $Time
#> 66 168 5 187 81 154 194 49 177 79 29 37 13
#> 22.13 23.72 16.43 9.92 14.06 12.63 22.40 12.19 12.53 16.23 15.45 12.52 14.34
#> 39 134 139 130 85 125 97 52 39.1 76 179 23 36
#> 15.59 17.81 21.49 16.47 16.44 15.65 19.14 10.42 15.59 19.22 18.63 16.92 21.19
#> 40 37.1 97.1 164 14 110 136 25 188 37.2 123 107 96
#> 18.00 12.52 19.14 23.60 12.89 17.56 21.83 6.32 16.16 12.52 13.00 11.18 14.54
#> 5.1 106 5.2 26 190 6 197 39.2 39.3 130.1 49.1 79.1 55
#> 16.43 16.67 16.43 15.77 20.81 15.64 21.60 15.59 15.59 16.47 12.19 16.23 19.34
#> 45 32 63 155 39.4 164.1 190.1 14.1 190.2 24 90 123.1 99
#> 17.42 20.90 22.77 13.08 15.59 23.60 20.81 12.89 20.81 23.89 20.94 13.00 21.19
#> 18 164.2 69 29.1 106.1 30 166 49.2 177.1 81.1 183 55.1 23.1
#> 15.21 23.60 23.23 15.45 16.67 17.43 19.98 12.19 12.53 14.06 9.24 19.34 16.92
#> 171 36.1 113 85.1 16 154.1 66.1 101 90.1 105 43 130.2 93
#> 16.57 21.19 22.86 16.44 8.71 12.63 22.13 9.97 20.94 19.75 12.10 16.47 10.33
#> 69.1 24.1 79.2 101.1 55.2 167 139.1 128 194.1 106.2 127 86 173
#> 23.23 23.89 16.23 9.97 19.34 15.55 21.49 20.35 22.40 16.67 3.53 23.81 24.00
#> 165 64 21 80 120 172 141 141.1 186 20 185 75 144
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 160 98 116 33 182 34 132 137 34.1 147 173.1 34.2 165.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 21.1 151 46 11 103 9 34.3 163 38 118 95 35 12
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 122 198 9.1 172.1 2 144.1 103.1 17 12.1 75.1 191 19 28
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 83 185.1 122.1 116.1 33.1 116.2 22 27 126 135 174 182.1 122.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 147.1 198.1 1 95.1 182.2 151.1 75.2 84 2.1 152 17.1 17.2 34.4
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165.2 34.5 104 112 135.1
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[86]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.006135661 0.505207512 0.163871000
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.386540597 -0.003563091 0.691252014
#> grade_iii, Cure model
#> 1.661115846
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 127 3.53 1 62 0 1
#> 199 19.81 1 NA 0 1
#> 105 19.75 1 60 0 0
#> 189 10.51 1 NA 1 0
#> 192 16.44 1 31 1 0
#> 40 18.00 1 28 1 0
#> 50 10.02 1 NA 1 0
#> 18 15.21 1 49 1 0
#> 158 20.14 1 74 1 0
#> 197 21.60 1 69 1 0
#> 57 14.46 1 45 0 1
#> 180 14.82 1 37 0 0
#> 166 19.98 1 48 0 0
#> 66 22.13 1 53 0 0
#> 169 22.41 1 46 0 0
#> 123 13.00 1 44 1 0
#> 85 16.44 1 36 0 0
#> 5 16.43 1 51 0 1
#> 36 21.19 1 48 0 1
#> 66.1 22.13 1 53 0 0
#> 194 22.40 1 38 0 1
#> 90 20.94 1 50 0 1
#> 92 22.92 1 47 0 1
#> 85.1 16.44 1 36 0 0
#> 140 12.68 1 59 1 0
#> 69 23.23 1 25 0 1
#> 153 21.33 1 55 1 0
#> 149 8.37 1 33 1 0
#> 14 12.89 1 21 0 0
#> 105.1 19.75 1 60 0 0
#> 59 10.16 1 NA 1 0
#> 150 20.33 1 48 0 0
#> 60 13.15 1 38 1 0
#> 164 23.60 1 76 0 1
#> 45 17.42 1 54 0 1
#> 171 16.57 1 41 0 1
#> 159 10.55 1 50 0 1
#> 58 19.34 1 39 0 0
#> 134 17.81 1 47 1 0
#> 13 14.34 1 54 0 1
#> 16 8.71 1 71 0 1
#> 96 14.54 1 33 0 1
#> 96.1 14.54 1 33 0 1
#> 154 12.63 1 20 1 0
#> 114 13.68 1 NA 0 0
#> 145 10.07 1 65 1 0
#> 36.1 21.19 1 48 0 1
#> 88 18.37 1 47 0 0
#> 89 11.44 1 NA 0 0
#> 149.1 8.37 1 33 1 0
#> 30 17.43 1 78 0 0
#> 18.1 15.21 1 49 1 0
#> 184 17.77 1 38 0 0
#> 90.1 20.94 1 50 0 1
#> 59.1 10.16 1 NA 1 0
#> 166.1 19.98 1 48 0 0
#> 40.1 18.00 1 28 1 0
#> 89.1 11.44 1 NA 0 0
#> 50.1 10.02 1 NA 1 0
#> 51 18.23 1 83 0 1
#> 37 12.52 1 57 1 0
#> 63 22.77 1 31 1 0
#> 164.1 23.60 1 76 0 1
#> 133 14.65 1 57 0 0
#> 130 16.47 1 53 0 1
#> 49 12.19 1 48 1 0
#> 37.1 12.52 1 57 1 0
#> 36.2 21.19 1 48 0 1
#> 155 13.08 1 26 0 0
#> 199.1 19.81 1 NA 0 1
#> 50.2 10.02 1 NA 1 0
#> 13.1 14.34 1 54 0 1
#> 6 15.64 1 39 0 0
#> 130.1 16.47 1 53 0 1
#> 175 21.91 1 43 0 0
#> 61 10.12 1 36 0 1
#> 86 23.81 1 58 0 1
#> 40.2 18.00 1 28 1 0
#> 59.2 10.16 1 NA 1 0
#> 139 21.49 1 63 1 0
#> 91 5.33 1 61 0 1
#> 32 20.90 1 37 1 0
#> 30.1 17.43 1 78 0 0
#> 157 15.10 1 47 0 0
#> 134.1 17.81 1 47 1 0
#> 134.2 17.81 1 47 1 0
#> 111 17.45 1 47 0 1
#> 91.1 5.33 1 61 0 1
#> 60.1 13.15 1 38 1 0
#> 5.1 16.43 1 51 0 1
#> 40.3 18.00 1 28 1 0
#> 155.1 13.08 1 26 0 0
#> 5.2 16.43 1 51 0 1
#> 117 17.46 1 26 0 1
#> 189.1 10.51 1 NA 1 0
#> 18.2 15.21 1 49 1 0
#> 79 16.23 1 54 1 0
#> 99 21.19 1 38 0 1
#> 78 23.88 1 43 0 0
#> 179 18.63 1 42 0 0
#> 77 7.27 1 67 0 1
#> 117.1 17.46 1 26 0 1
#> 91.2 5.33 1 61 0 1
#> 170 19.54 1 43 0 1
#> 6.1 15.64 1 39 0 0
#> 123.1 13.00 1 44 1 0
#> 50.3 10.02 1 NA 1 0
#> 66.2 22.13 1 53 0 0
#> 61.1 10.12 1 36 0 1
#> 37.2 12.52 1 57 1 0
#> 43 12.10 1 61 0 1
#> 89.2 11.44 1 NA 0 0
#> 80 24.00 0 41 0 0
#> 120 24.00 0 68 0 1
#> 109 24.00 0 48 0 0
#> 120.1 24.00 0 68 0 1
#> 131 24.00 0 66 0 0
#> 102 24.00 0 49 0 0
#> 67 24.00 0 25 0 0
#> 143 24.00 0 51 0 0
#> 122 24.00 0 66 0 0
#> 165 24.00 0 47 0 0
#> 31 24.00 0 36 0 1
#> 186 24.00 0 45 1 0
#> 53 24.00 0 32 0 1
#> 62 24.00 0 71 0 0
#> 120.2 24.00 0 68 0 1
#> 34 24.00 0 36 0 0
#> 71 24.00 0 51 0 0
#> 148 24.00 0 61 1 0
#> 162 24.00 0 51 0 0
#> 27 24.00 0 63 1 0
#> 9 24.00 0 31 1 0
#> 64 24.00 0 43 0 0
#> 9.1 24.00 0 31 1 0
#> 17 24.00 0 38 0 1
#> 200 24.00 0 64 0 0
#> 7 24.00 0 37 1 0
#> 121 24.00 0 57 1 0
#> 200.1 24.00 0 64 0 0
#> 27.1 24.00 0 63 1 0
#> 22 24.00 0 52 1 0
#> 83 24.00 0 6 0 0
#> 104 24.00 0 50 1 0
#> 94 24.00 0 51 0 1
#> 156 24.00 0 50 1 0
#> 182 24.00 0 35 0 0
#> 2 24.00 0 9 0 0
#> 142 24.00 0 53 0 0
#> 143.1 24.00 0 51 0 0
#> 135 24.00 0 58 1 0
#> 172 24.00 0 41 0 0
#> 135.1 24.00 0 58 1 0
#> 193 24.00 0 45 0 1
#> 162.1 24.00 0 51 0 0
#> 44 24.00 0 56 0 0
#> 152 24.00 0 36 0 1
#> 137 24.00 0 45 1 0
#> 126 24.00 0 48 0 0
#> 143.2 24.00 0 51 0 0
#> 173 24.00 0 19 0 1
#> 132 24.00 0 55 0 0
#> 64.1 24.00 0 43 0 0
#> 176 24.00 0 43 0 1
#> 65 24.00 0 57 1 0
#> 137.1 24.00 0 45 1 0
#> 112 24.00 0 61 0 0
#> 22.1 24.00 0 52 1 0
#> 28 24.00 0 67 1 0
#> 82 24.00 0 34 0 0
#> 132.1 24.00 0 55 0 0
#> 131.1 24.00 0 66 0 0
#> 12 24.00 0 63 0 0
#> 131.2 24.00 0 66 0 0
#> 67.1 24.00 0 25 0 0
#> 185 24.00 0 44 1 0
#> 109.1 24.00 0 48 0 0
#> 142.1 24.00 0 53 0 0
#> 163 24.00 0 66 0 0
#> 172.1 24.00 0 41 0 0
#> 27.2 24.00 0 63 1 0
#> 126.1 24.00 0 48 0 0
#> 33 24.00 0 53 0 0
#> 94.1 24.00 0 51 0 1
#> 75 24.00 0 21 1 0
#> 143.3 24.00 0 51 0 0
#> 126.2 24.00 0 48 0 0
#> 132.2 24.00 0 55 0 0
#> 182.1 24.00 0 35 0 0
#> 28.1 24.00 0 67 1 0
#> 118 24.00 0 44 1 0
#> 186.1 24.00 0 45 1 0
#> 73 24.00 0 NA 0 1
#> 87 24.00 0 27 0 0
#> 82.1 24.00 0 34 0 0
#> 75.1 24.00 0 21 1 0
#> 102.1 24.00 0 49 0 0
#> 186.2 24.00 0 45 1 0
#> 17.1 24.00 0 38 0 1
#> 38 24.00 0 31 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.387 NA NA NA
#> 2 age, Cure model -0.00356 NA NA NA
#> 3 grade_ii, Cure model 0.691 NA NA NA
#> 4 grade_iii, Cure model 1.66 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00614 NA NA NA
#> 2 grade_ii, Survival model 0.505 NA NA NA
#> 3 grade_iii, Survival model 0.164 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.386541 -0.003563 0.691252 1.661116
#>
#> Degrees of Freedom: 183 Total (i.e. Null); 180 Residual
#> Null Deviance: 254.5
#> Residual Deviance: 235.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.386540597 -0.003563091 0.691252014 1.661115846
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.006135661 0.505207512 0.163871000
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.989337945 0.259940032 0.511198388 0.335879214 0.606539957 0.229083607
#> [7] 0.119902223 0.691787715 0.648753852 0.239369043 0.081531930 0.062507346
#> [13] 0.767143212 0.511198388 0.542656697 0.150705702 0.081531930 0.071976705
#> [19] 0.188402100 0.043642060 0.511198388 0.799246744 0.034159534 0.140562165
#> [25] 0.926200073 0.788484947 0.259940032 0.218773950 0.724233642 0.017812150
#> [31] 0.468759816 0.479378442 0.873223554 0.291813148 0.376363784 0.702624731
#> [37] 0.915562224 0.670318878 0.670318878 0.809986280 0.904953707 0.150705702
#> [43] 0.313648992 0.926200073 0.447835365 0.606539957 0.406558504 0.188402100
#> [49] 0.239369043 0.335879214 0.324708531 0.820659880 0.053379943 0.017812150
#> [55] 0.659510351 0.490016861 0.852062751 0.820659880 0.150705702 0.745642896
#> [61] 0.702624731 0.585103670 0.490016861 0.109444293 0.883833408 0.009509546
#> [67] 0.335879214 0.130283546 0.957760799 0.208586827 0.447835365 0.638033456
#> [73] 0.376363784 0.376363784 0.437435103 0.957760799 0.724233642 0.542656697
#> [79] 0.335879214 0.745642896 0.542656697 0.416938233 0.606539957 0.574370028
#> [85] 0.150705702 0.002586705 0.302686323 0.947184177 0.416938233 0.957760799
#> [91] 0.281025550 0.585103670 0.767143212 0.081531930 0.883833408 0.820659880
#> [97] 0.862630840 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 127 105 192 40 18 158 197 57 180 166 66 169 123
#> 3.53 19.75 16.44 18.00 15.21 20.14 21.60 14.46 14.82 19.98 22.13 22.41 13.00
#> 85 5 36 66.1 194 90 92 85.1 140 69 153 149 14
#> 16.44 16.43 21.19 22.13 22.40 20.94 22.92 16.44 12.68 23.23 21.33 8.37 12.89
#> 105.1 150 60 164 45 171 159 58 134 13 16 96 96.1
#> 19.75 20.33 13.15 23.60 17.42 16.57 10.55 19.34 17.81 14.34 8.71 14.54 14.54
#> 154 145 36.1 88 149.1 30 18.1 184 90.1 166.1 40.1 51 37
#> 12.63 10.07 21.19 18.37 8.37 17.43 15.21 17.77 20.94 19.98 18.00 18.23 12.52
#> 63 164.1 133 130 49 37.1 36.2 155 13.1 6 130.1 175 61
#> 22.77 23.60 14.65 16.47 12.19 12.52 21.19 13.08 14.34 15.64 16.47 21.91 10.12
#> 86 40.2 139 91 32 30.1 157 134.1 134.2 111 91.1 60.1 5.1
#> 23.81 18.00 21.49 5.33 20.90 17.43 15.10 17.81 17.81 17.45 5.33 13.15 16.43
#> 40.3 155.1 5.2 117 18.2 79 99 78 179 77 117.1 91.2 170
#> 18.00 13.08 16.43 17.46 15.21 16.23 21.19 23.88 18.63 7.27 17.46 5.33 19.54
#> 6.1 123.1 66.2 61.1 37.2 43 80 120 109 120.1 131 102 67
#> 15.64 13.00 22.13 10.12 12.52 12.10 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143 122 165 31 186 53 62 120.2 34 71 148 162 27
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9 64 9.1 17 200 7 121 200.1 27.1 22 83 104 94
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156 182 2 142 143.1 135 172 135.1 193 162.1 44 152 137
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126 143.2 173 132 64.1 176 65 137.1 112 22.1 28 82 132.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131.1 12 131.2 67.1 185 109.1 142.1 163 172.1 27.2 126.1 33 94.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75 143.3 126.2 132.2 182.1 28.1 118 186.1 87 82.1 75.1 102.1 186.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 17.1 38
#> 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[87]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.006709197 0.682933776 0.509184977
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.45963343 0.02659631 -0.08359951
#> grade_iii, Cure model
#> 1.22453993
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 66 22.13 1 53 0 0
#> 158 20.14 1 74 1 0
#> 89 11.44 1 NA 0 0
#> 158.1 20.14 1 74 1 0
#> 114 13.68 1 NA 0 0
#> 188 16.16 1 46 0 1
#> 136 21.83 1 43 0 1
#> 128 20.35 1 35 0 1
#> 129 23.41 1 53 1 0
#> 79 16.23 1 54 1 0
#> 150 20.33 1 48 0 0
#> 30 17.43 1 78 0 0
#> 97 19.14 1 65 0 1
#> 169 22.41 1 46 0 0
#> 43 12.10 1 61 0 1
#> 111 17.45 1 47 0 1
#> 184 17.77 1 38 0 0
#> 168 23.72 1 70 0 0
#> 177 12.53 1 75 0 0
#> 129.1 23.41 1 53 1 0
#> 123 13.00 1 44 1 0
#> 164 23.60 1 76 0 1
#> 171 16.57 1 41 0 1
#> 89.1 11.44 1 NA 0 0
#> 124 9.73 1 NA 1 0
#> 23 16.92 1 61 0 0
#> 128.1 20.35 1 35 0 1
#> 24 23.89 1 38 0 0
#> 158.2 20.14 1 74 1 0
#> 15 22.68 1 48 0 0
#> 190 20.81 1 42 1 0
#> 79.1 16.23 1 54 1 0
#> 114.1 13.68 1 NA 0 0
#> 155 13.08 1 26 0 0
#> 107 11.18 1 54 1 0
#> 177.1 12.53 1 75 0 0
#> 167 15.55 1 56 1 0
#> 69 23.23 1 25 0 1
#> 127 3.53 1 62 0 1
#> 153 21.33 1 55 1 0
#> 107.1 11.18 1 54 1 0
#> 108 18.29 1 39 0 1
#> 57 14.46 1 45 0 1
#> 107.2 11.18 1 54 1 0
#> 145 10.07 1 65 1 0
#> 32 20.90 1 37 1 0
#> 130 16.47 1 53 0 1
#> 4 17.64 1 NA 0 1
#> 181 16.46 1 45 0 1
#> 63 22.77 1 31 1 0
#> 108.1 18.29 1 39 0 1
#> 77 7.27 1 67 0 1
#> 136.1 21.83 1 43 0 1
#> 36 21.19 1 48 0 1
#> 194 22.40 1 38 0 1
#> 78 23.88 1 43 0 0
#> 177.2 12.53 1 75 0 0
#> 86 23.81 1 58 0 1
#> 23.1 16.92 1 61 0 0
#> 8 18.43 1 32 0 0
#> 24.1 23.89 1 38 0 0
#> 199 19.81 1 NA 0 1
#> 61 10.12 1 36 0 1
#> 111.1 17.45 1 47 0 1
#> 159 10.55 1 50 0 1
#> 127.1 3.53 1 62 0 1
#> 63.1 22.77 1 31 1 0
#> 96 14.54 1 33 0 1
#> 40 18.00 1 28 1 0
#> 45 17.42 1 54 0 1
#> 124.1 9.73 1 NA 1 0
#> 128.2 20.35 1 35 0 1
#> 70 7.38 1 30 1 0
#> 130.1 16.47 1 53 0 1
#> 124.2 9.73 1 NA 1 0
#> 113 22.86 1 34 0 0
#> 181.1 16.46 1 45 0 1
#> 36.1 21.19 1 48 0 1
#> 107.3 11.18 1 54 1 0
#> 128.3 20.35 1 35 0 1
#> 69.1 23.23 1 25 0 1
#> 189 10.51 1 NA 1 0
#> 134 17.81 1 47 1 0
#> 177.3 12.53 1 75 0 0
#> 36.2 21.19 1 48 0 1
#> 36.3 21.19 1 48 0 1
#> 164.1 23.60 1 76 0 1
#> 159.1 10.55 1 50 0 1
#> 150.1 20.33 1 48 0 0
#> 106 16.67 1 49 1 0
#> 197 21.60 1 69 1 0
#> 189.1 10.51 1 NA 1 0
#> 5 16.43 1 51 0 1
#> 105 19.75 1 60 0 0
#> 29 15.45 1 68 1 0
#> 111.2 17.45 1 47 0 1
#> 49 12.19 1 48 1 0
#> 15.1 22.68 1 48 0 0
#> 86.1 23.81 1 58 0 1
#> 36.4 21.19 1 48 0 1
#> 51 18.23 1 83 0 1
#> 199.1 19.81 1 NA 0 1
#> 58 19.34 1 39 0 0
#> 70.1 7.38 1 30 1 0
#> 39 15.59 1 37 0 1
#> 26 15.77 1 49 0 1
#> 123.1 13.00 1 44 1 0
#> 92 22.92 1 47 0 1
#> 24.2 23.89 1 38 0 0
#> 117 17.46 1 26 0 1
#> 113.1 22.86 1 34 0 0
#> 129.2 23.41 1 53 1 0
#> 172 24.00 0 41 0 0
#> 120 24.00 0 68 0 1
#> 148 24.00 0 61 1 0
#> 141 24.00 0 44 1 0
#> 9 24.00 0 31 1 0
#> 84 24.00 0 39 0 1
#> 28 24.00 0 67 1 0
#> 82 24.00 0 34 0 0
#> 162 24.00 0 51 0 0
#> 182 24.00 0 35 0 0
#> 182.1 24.00 0 35 0 0
#> 178 24.00 0 52 1 0
#> 103 24.00 0 56 1 0
#> 98 24.00 0 34 1 0
#> 186 24.00 0 45 1 0
#> 73 24.00 0 NA 0 1
#> 142 24.00 0 53 0 0
#> 156 24.00 0 50 1 0
#> 65 24.00 0 57 1 0
#> 54 24.00 0 53 1 0
#> 33 24.00 0 53 0 0
#> 75 24.00 0 21 1 0
#> 102 24.00 0 49 0 0
#> 156.1 24.00 0 50 1 0
#> 73.1 24.00 0 NA 0 1
#> 144 24.00 0 28 0 1
#> 146 24.00 0 63 1 0
#> 172.1 24.00 0 41 0 0
#> 72 24.00 0 40 0 1
#> 141.1 24.00 0 44 1 0
#> 109 24.00 0 48 0 0
#> 12 24.00 0 63 0 0
#> 162.1 24.00 0 51 0 0
#> 3 24.00 0 31 1 0
#> 148.1 24.00 0 61 1 0
#> 182.2 24.00 0 35 0 0
#> 173 24.00 0 19 0 1
#> 196 24.00 0 19 0 0
#> 191 24.00 0 60 0 1
#> 80 24.00 0 41 0 0
#> 116 24.00 0 58 0 1
#> 48 24.00 0 31 1 0
#> 156.2 24.00 0 50 1 0
#> 80.1 24.00 0 41 0 0
#> 35 24.00 0 51 0 0
#> 71 24.00 0 51 0 0
#> 115 24.00 0 NA 1 0
#> 156.3 24.00 0 50 1 0
#> 83 24.00 0 6 0 0
#> 104 24.00 0 50 1 0
#> 82.1 24.00 0 34 0 0
#> 121 24.00 0 57 1 0
#> 72.1 24.00 0 40 0 1
#> 38 24.00 0 31 1 0
#> 120.1 24.00 0 68 0 1
#> 162.2 24.00 0 51 0 0
#> 120.2 24.00 0 68 0 1
#> 193 24.00 0 45 0 1
#> 47 24.00 0 38 0 1
#> 147 24.00 0 76 1 0
#> 80.2 24.00 0 41 0 0
#> 198 24.00 0 66 0 1
#> 151 24.00 0 42 0 0
#> 48.1 24.00 0 31 1 0
#> 98.1 24.00 0 34 1 0
#> 38.1 24.00 0 31 1 0
#> 122 24.00 0 66 0 0
#> 71.1 24.00 0 51 0 0
#> 160 24.00 0 31 1 0
#> 71.2 24.00 0 51 0 0
#> 84.1 24.00 0 39 0 1
#> 20 24.00 0 46 1 0
#> 126 24.00 0 48 0 0
#> 173.1 24.00 0 19 0 1
#> 54.1 24.00 0 53 1 0
#> 135 24.00 0 58 1 0
#> 119 24.00 0 17 0 0
#> 47.1 24.00 0 38 0 1
#> 34 24.00 0 36 0 0
#> 34.1 24.00 0 36 0 0
#> 75.1 24.00 0 21 1 0
#> 94 24.00 0 51 0 1
#> 20.1 24.00 0 46 1 0
#> 118 24.00 0 44 1 0
#> 28.1 24.00 0 67 1 0
#> 33.1 24.00 0 53 0 0
#> 156.4 24.00 0 50 1 0
#> 156.5 24.00 0 50 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.46 NA NA NA
#> 2 age, Cure model 0.0266 NA NA NA
#> 3 grade_ii, Cure model -0.0836 NA NA NA
#> 4 grade_iii, Cure model 1.22 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00671 NA NA NA
#> 2 grade_ii, Survival model 0.683 NA NA NA
#> 3 grade_iii, Survival model 0.509 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.4596 0.0266 -0.0836 1.2245
#>
#> Degrees of Freedom: 184 Total (i.e. Null); 181 Residual
#> Null Deviance: 255.2
#> Residual Deviance: 235.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.45963343 0.02659631 -0.08359951 1.22453993
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.006709197 0.682933776 0.509184977
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.50907427 0.66534647 0.66534647 0.85661346 0.52001427 0.61918254
#> [7] 0.33561574 0.84551900 0.64992782 0.78010152 0.70095536 0.48670356
#> [13] 0.93470500 0.76147068 0.74848407 0.27443659 0.90966463 0.33561574
#> [19] 0.89944220 0.29888945 0.81068881 0.79248578 0.61918254 0.08562422
#> [25] 0.66534647 0.46412068 0.61088518 0.84551900 0.89421756 0.93966822
#> [31] 0.90966463 0.87304245 0.37711548 0.99105277 0.55060697 0.93966822
#> [37] 0.71496815 0.88898710 0.93966822 0.97272475 0.60240066 0.81666559
#> [43] 0.82834139 0.44111276 0.71496815 0.98650640 0.52001427 0.56026977
#> [49] 0.49803297 0.18584701 0.90966463 0.22520798 0.79248578 0.70797006
#> [55] 0.08562422 0.96803636 0.76147068 0.95863145 0.99105277 0.44111276
#> [61] 0.88371787 0.73530939 0.78632755 0.61918254 0.97736701 0.81666559
#> [67] 0.41624094 0.82834139 0.56026977 0.93966822 0.61918254 0.37711548
#> [73] 0.74194684 0.90966463 0.56026977 0.56026977 0.29888945 0.95863145
#> [79] 0.64992782 0.80465909 0.54061755 0.83981497 0.68667955 0.87841461
#> [85] 0.76147068 0.92970177 0.46412068 0.22520798 0.56026977 0.72858767
#> [91] 0.69382844 0.97736701 0.86760734 0.86213338 0.89944220 0.40341434
#> [97] 0.08562422 0.75500477 0.41624094 0.33561574 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 66 158 158.1 188 136 128 129 79 150 30 97 169 43
#> 22.13 20.14 20.14 16.16 21.83 20.35 23.41 16.23 20.33 17.43 19.14 22.41 12.10
#> 111 184 168 177 129.1 123 164 171 23 128.1 24 158.2 15
#> 17.45 17.77 23.72 12.53 23.41 13.00 23.60 16.57 16.92 20.35 23.89 20.14 22.68
#> 190 79.1 155 107 177.1 167 69 127 153 107.1 108 57 107.2
#> 20.81 16.23 13.08 11.18 12.53 15.55 23.23 3.53 21.33 11.18 18.29 14.46 11.18
#> 145 32 130 181 63 108.1 77 136.1 36 194 78 177.2 86
#> 10.07 20.90 16.47 16.46 22.77 18.29 7.27 21.83 21.19 22.40 23.88 12.53 23.81
#> 23.1 8 24.1 61 111.1 159 127.1 63.1 96 40 45 128.2 70
#> 16.92 18.43 23.89 10.12 17.45 10.55 3.53 22.77 14.54 18.00 17.42 20.35 7.38
#> 130.1 113 181.1 36.1 107.3 128.3 69.1 134 177.3 36.2 36.3 164.1 159.1
#> 16.47 22.86 16.46 21.19 11.18 20.35 23.23 17.81 12.53 21.19 21.19 23.60 10.55
#> 150.1 106 197 5 105 29 111.2 49 15.1 86.1 36.4 51 58
#> 20.33 16.67 21.60 16.43 19.75 15.45 17.45 12.19 22.68 23.81 21.19 18.23 19.34
#> 70.1 39 26 123.1 92 24.2 117 113.1 129.2 172 120 148 141
#> 7.38 15.59 15.77 13.00 22.92 23.89 17.46 22.86 23.41 24.00 24.00 24.00 24.00
#> 9 84 28 82 162 182 182.1 178 103 98 186 142 156
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 65 54 33 75 102 156.1 144 146 172.1 72 141.1 109 12
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 162.1 3 148.1 182.2 173 196 191 80 116 48 156.2 80.1 35
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71 156.3 83 104 82.1 121 72.1 38 120.1 162.2 120.2 193 47
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 147 80.2 198 151 48.1 98.1 38.1 122 71.1 160 71.2 84.1 20
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126 173.1 54.1 135 119 47.1 34 34.1 75.1 94 20.1 118 28.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33.1 156.4 156.5
#> 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[88]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01050727 0.83577353 0.72745653
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.83317774 0.01762709 -0.14485929
#> grade_iii, Cure model
#> 0.90467650
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 175 21.91 1 43 0 0
#> 114 13.68 1 NA 0 0
#> 187 9.92 1 39 1 0
#> 81 14.06 1 34 0 0
#> 107 11.18 1 54 1 0
#> 164 23.60 1 76 0 1
#> 159 10.55 1 50 0 1
#> 86 23.81 1 58 0 1
#> 42 12.43 1 49 0 1
#> 188 16.16 1 46 0 1
#> 108 18.29 1 39 0 1
#> 181 16.46 1 45 0 1
#> 168 23.72 1 70 0 0
#> 51 18.23 1 83 0 1
#> 125 15.65 1 67 1 0
#> 153 21.33 1 55 1 0
#> 179 18.63 1 42 0 0
#> 197 21.60 1 69 1 0
#> 179.1 18.63 1 42 0 0
#> 105 19.75 1 60 0 0
#> 37 12.52 1 57 1 0
#> 129 23.41 1 53 1 0
#> 10 10.53 1 34 0 0
#> 170 19.54 1 43 0 1
#> 117 17.46 1 26 0 1
#> 108.1 18.29 1 39 0 1
#> 36 21.19 1 48 0 1
#> 105.1 19.75 1 60 0 0
#> 52 10.42 1 52 0 1
#> 78 23.88 1 43 0 0
#> 195 11.76 1 NA 1 0
#> 159.1 10.55 1 50 0 1
#> 96 14.54 1 33 0 1
#> 106 16.67 1 49 1 0
#> 167 15.55 1 56 1 0
#> 52.1 10.42 1 52 0 1
#> 108.2 18.29 1 39 0 1
#> 101 9.97 1 10 0 1
#> 57 14.46 1 45 0 1
#> 169 22.41 1 46 0 0
#> 123 13.00 1 44 1 0
#> 168.1 23.72 1 70 0 0
#> 13 14.34 1 54 0 1
#> 45 17.42 1 54 0 1
#> 15 22.68 1 48 0 0
#> 23 16.92 1 61 0 0
#> 32 20.90 1 37 1 0
#> 13.1 14.34 1 54 0 1
#> 66 22.13 1 53 0 0
#> 123.1 13.00 1 44 1 0
#> 167.1 15.55 1 56 1 0
#> 50 10.02 1 NA 1 0
#> 105.2 19.75 1 60 0 0
#> 81.1 14.06 1 34 0 0
#> 181.1 16.46 1 45 0 1
#> 24 23.89 1 38 0 0
#> 101.1 9.97 1 10 0 1
#> 130 16.47 1 53 0 1
#> 100 16.07 1 60 0 0
#> 154 12.63 1 20 1 0
#> 63 22.77 1 31 1 0
#> 105.3 19.75 1 60 0 0
#> 81.2 14.06 1 34 0 0
#> 171 16.57 1 41 0 1
#> 154.1 12.63 1 20 1 0
#> 36.1 21.19 1 48 0 1
#> 171.1 16.57 1 41 0 1
#> 15.1 22.68 1 48 0 0
#> 169.1 22.41 1 46 0 0
#> 8 18.43 1 32 0 0
#> 183 9.24 1 67 1 0
#> 10.1 10.53 1 34 0 0
#> 106.1 16.67 1 49 1 0
#> 108.3 18.29 1 39 0 1
#> 114.1 13.68 1 NA 0 0
#> 149 8.37 1 33 1 0
#> 70 7.38 1 30 1 0
#> 199 19.81 1 NA 0 1
#> 49 12.19 1 48 1 0
#> 63.1 22.77 1 31 1 0
#> 36.2 21.19 1 48 0 1
#> 97 19.14 1 65 0 1
#> 57.1 14.46 1 45 0 1
#> 43 12.10 1 61 0 1
#> 55 19.34 1 69 0 1
#> 189 10.51 1 NA 1 0
#> 8.1 18.43 1 32 0 0
#> 170.1 19.54 1 43 0 1
#> 187.1 9.92 1 39 1 0
#> 149.1 8.37 1 33 1 0
#> 30 17.43 1 78 0 0
#> 85 16.44 1 36 0 0
#> 30.1 17.43 1 78 0 0
#> 149.2 8.37 1 33 1 0
#> 171.2 16.57 1 41 0 1
#> 175.1 21.91 1 43 0 0
#> 32.1 20.90 1 37 1 0
#> 107.1 11.18 1 54 1 0
#> 192 16.44 1 31 1 0
#> 175.2 21.91 1 43 0 0
#> 78.1 23.88 1 43 0 0
#> 30.2 17.43 1 78 0 0
#> 110 17.56 1 65 0 1
#> 124 9.73 1 NA 1 0
#> 66.1 22.13 1 53 0 0
#> 68 20.62 1 44 0 0
#> 57.2 14.46 1 45 0 1
#> 111 17.45 1 47 0 1
#> 166 19.98 1 48 0 0
#> 145 10.07 1 65 1 0
#> 56 12.21 1 60 0 0
#> 36.3 21.19 1 48 0 1
#> 17 24.00 0 38 0 1
#> 193 24.00 0 45 0 1
#> 163 24.00 0 66 0 0
#> 152 24.00 0 36 0 1
#> 38 24.00 0 31 1 0
#> 165 24.00 0 47 0 0
#> 20 24.00 0 46 1 0
#> 138 24.00 0 44 1 0
#> 72 24.00 0 40 0 1
#> 9 24.00 0 31 1 0
#> 33 24.00 0 53 0 0
#> 9.1 24.00 0 31 1 0
#> 64 24.00 0 43 0 0
#> 138.1 24.00 0 44 1 0
#> 165.1 24.00 0 47 0 0
#> 146 24.00 0 63 1 0
#> 172 24.00 0 41 0 0
#> 156 24.00 0 50 1 0
#> 200 24.00 0 64 0 0
#> 54 24.00 0 53 1 0
#> 72.1 24.00 0 40 0 1
#> 75 24.00 0 21 1 0
#> 9.2 24.00 0 31 1 0
#> 118 24.00 0 44 1 0
#> 33.1 24.00 0 53 0 0
#> 176 24.00 0 43 0 1
#> 126 24.00 0 48 0 0
#> 22 24.00 0 52 1 0
#> 9.3 24.00 0 31 1 0
#> 143 24.00 0 51 0 0
#> 21 24.00 0 47 0 0
#> 102 24.00 0 49 0 0
#> 118.1 24.00 0 44 1 0
#> 38.1 24.00 0 31 1 0
#> 9.4 24.00 0 31 1 0
#> 200.1 24.00 0 64 0 0
#> 178 24.00 0 52 1 0
#> 151 24.00 0 42 0 0
#> 34 24.00 0 36 0 0
#> 72.2 24.00 0 40 0 1
#> 178.1 24.00 0 52 1 0
#> 35 24.00 0 51 0 0
#> 165.2 24.00 0 47 0 0
#> 65 24.00 0 57 1 0
#> 135 24.00 0 58 1 0
#> 174 24.00 0 49 1 0
#> 172.1 24.00 0 41 0 0
#> 34.1 24.00 0 36 0 0
#> 104 24.00 0 50 1 0
#> 115 24.00 0 NA 1 0
#> 62 24.00 0 71 0 0
#> 9.5 24.00 0 31 1 0
#> 112 24.00 0 61 0 0
#> 7 24.00 0 37 1 0
#> 9.6 24.00 0 31 1 0
#> 186 24.00 0 45 1 0
#> 178.2 24.00 0 52 1 0
#> 200.2 24.00 0 64 0 0
#> 12 24.00 0 63 0 0
#> 135.1 24.00 0 58 1 0
#> 84 24.00 0 39 0 1
#> 44 24.00 0 56 0 0
#> 161 24.00 0 45 0 0
#> 172.2 24.00 0 41 0 0
#> 121 24.00 0 57 1 0
#> 118.2 24.00 0 44 1 0
#> 109 24.00 0 48 0 0
#> 28 24.00 0 67 1 0
#> 74 24.00 0 43 0 1
#> 2 24.00 0 9 0 0
#> 144 24.00 0 28 0 1
#> 53 24.00 0 32 0 1
#> 191 24.00 0 60 0 1
#> 173 24.00 0 19 0 1
#> 126.1 24.00 0 48 0 0
#> 38.2 24.00 0 31 1 0
#> 11 24.00 0 42 0 1
#> 165.3 24.00 0 47 0 0
#> 162 24.00 0 51 0 0
#> 11.1 24.00 0 42 0 1
#> 126.2 24.00 0 48 0 0
#> 182 24.00 0 35 0 0
#> 135.2 24.00 0 58 1 0
#> 47 24.00 0 38 0 1
#> 193.1 24.00 0 45 0 1
#> 22.1 24.00 0 52 1 0
#> 143.1 24.00 0 51 0 0
#> 196 24.00 0 19 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.833 NA NA NA
#> 2 age, Cure model 0.0176 NA NA NA
#> 3 grade_ii, Cure model -0.145 NA NA NA
#> 4 grade_iii, Cure model 0.905 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0105 NA NA NA
#> 2 grade_ii, Survival model 0.836 NA NA NA
#> 3 grade_iii, Survival model 0.727 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.83318 0.01763 -0.14486 0.90468
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.5
#> Residual Deviance: 253.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.83317774 0.01762709 -0.14485929 0.90467650
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01050727 0.83577353 0.72745653
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.140716815 0.938679211 0.726168292 0.838526758 0.048204664 0.856823733
#> [7] 0.021179671 0.801419741 0.620382306 0.390885302 0.581246231 0.029337808
#> [13] 0.430037405 0.640036279 0.182536990 0.349429800 0.171626399 0.349429800
#> [19] 0.269051535 0.792131852 0.058974912 0.875033636 0.308829307 0.450373654
#> [25] 0.390885302 0.193259289 0.269051535 0.893358103 0.007569327 0.856823733
#> [31] 0.669248273 0.521420160 0.649877738 0.893358103 0.390885302 0.920764288
#> [37] 0.678939201 0.102440096 0.754688873 0.029337808 0.707252629 0.500735624
#> [43] 0.085150516 0.511028368 0.230824945 0.707252629 0.120930717 0.754688873
#> [49] 0.649877738 0.269051535 0.726168292 0.581246231 0.001704648 0.920764288
#> [55] 0.571251412 0.630173461 0.773607272 0.069153786 0.269051535 0.726168292
#> [61] 0.541694044 0.773607272 0.193259289 0.541694044 0.085150516 0.102440096
#> [67] 0.369991665 0.956414380 0.875033636 0.521420160 0.390885302 0.965311785
#> [73] 0.991309545 0.819994419 0.069153786 0.193259289 0.339210969 0.678939201
#> [79] 0.829265266 0.328978140 0.369991665 0.308829307 0.938679211 0.965311785
#> [85] 0.470381712 0.600870062 0.470381712 0.965311785 0.541694044 0.140716815
#> [91] 0.230824945 0.838526758 0.600870062 0.140716815 0.007569327 0.470381712
#> [97] 0.440210866 0.120930717 0.249546030 0.678939201 0.460406279 0.259226104
#> [103] 0.911608275 0.810682202 0.193259289 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 175 187 81 107 164 159 86 42 188 108 181 168 51
#> 21.91 9.92 14.06 11.18 23.60 10.55 23.81 12.43 16.16 18.29 16.46 23.72 18.23
#> 125 153 179 197 179.1 105 37 129 10 170 117 108.1 36
#> 15.65 21.33 18.63 21.60 18.63 19.75 12.52 23.41 10.53 19.54 17.46 18.29 21.19
#> 105.1 52 78 159.1 96 106 167 52.1 108.2 101 57 169 123
#> 19.75 10.42 23.88 10.55 14.54 16.67 15.55 10.42 18.29 9.97 14.46 22.41 13.00
#> 168.1 13 45 15 23 32 13.1 66 123.1 167.1 105.2 81.1 181.1
#> 23.72 14.34 17.42 22.68 16.92 20.90 14.34 22.13 13.00 15.55 19.75 14.06 16.46
#> 24 101.1 130 100 154 63 105.3 81.2 171 154.1 36.1 171.1 15.1
#> 23.89 9.97 16.47 16.07 12.63 22.77 19.75 14.06 16.57 12.63 21.19 16.57 22.68
#> 169.1 8 183 10.1 106.1 108.3 149 70 49 63.1 36.2 97 57.1
#> 22.41 18.43 9.24 10.53 16.67 18.29 8.37 7.38 12.19 22.77 21.19 19.14 14.46
#> 43 55 8.1 170.1 187.1 149.1 30 85 30.1 149.2 171.2 175.1 32.1
#> 12.10 19.34 18.43 19.54 9.92 8.37 17.43 16.44 17.43 8.37 16.57 21.91 20.90
#> 107.1 192 175.2 78.1 30.2 110 66.1 68 57.2 111 166 145 56
#> 11.18 16.44 21.91 23.88 17.43 17.56 22.13 20.62 14.46 17.45 19.98 10.07 12.21
#> 36.3 17 193 163 152 38 165 20 138 72 9 33 9.1
#> 21.19 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64 138.1 165.1 146 172 156 200 54 72.1 75 9.2 118 33.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176 126 22 9.3 143 21 102 118.1 38.1 9.4 200.1 178 151
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34 72.2 178.1 35 165.2 65 135 174 172.1 34.1 104 62 9.5
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 112 7 9.6 186 178.2 200.2 12 135.1 84 44 161 172.2 121
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 118.2 109 28 74 2 144 53 191 173 126.1 38.2 11 165.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 162 11.1 126.2 182 135.2 47 193.1 22.1 143.1 196
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[89]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.00395153 0.30958035 0.46726968
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.606066809 -0.007234769 -0.601123361
#> grade_iii, Cure model
#> 0.448020075
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 59 10.16 1 NA 1 0
#> 167 15.55 1 56 1 0
#> 41 18.02 1 40 1 0
#> 171 16.57 1 41 0 1
#> 69 23.23 1 25 0 1
#> 153 21.33 1 55 1 0
#> 14 12.89 1 21 0 0
#> 93 10.33 1 52 0 1
#> 124 9.73 1 NA 1 0
#> 129 23.41 1 53 1 0
#> 77 7.27 1 67 0 1
#> 41.1 18.02 1 40 1 0
#> 101 9.97 1 10 0 1
#> 41.2 18.02 1 40 1 0
#> 130 16.47 1 53 0 1
#> 157 15.10 1 47 0 0
#> 52 10.42 1 52 0 1
#> 127 3.53 1 62 0 1
#> 110 17.56 1 65 0 1
#> 26 15.77 1 49 0 1
#> 90 20.94 1 50 0 1
#> 113 22.86 1 34 0 0
#> 166 19.98 1 48 0 0
#> 157.1 15.10 1 47 0 0
#> 149 8.37 1 33 1 0
#> 30 17.43 1 78 0 0
#> 4 17.64 1 NA 0 1
#> 123 13.00 1 44 1 0
#> 99 21.19 1 38 0 1
#> 110.1 17.56 1 65 0 1
#> 58 19.34 1 39 0 0
#> 190 20.81 1 42 1 0
#> 91 5.33 1 61 0 1
#> 51 18.23 1 83 0 1
#> 170 19.54 1 43 0 1
#> 199 19.81 1 NA 0 1
#> 40 18.00 1 28 1 0
#> 91.1 5.33 1 61 0 1
#> 66 22.13 1 53 0 0
#> 68 20.62 1 44 0 0
#> 111 17.45 1 47 0 1
#> 85 16.44 1 36 0 0
#> 25 6.32 1 34 1 0
#> 150 20.33 1 48 0 0
#> 85.1 16.44 1 36 0 0
#> 129.1 23.41 1 53 1 0
#> 69.1 23.23 1 25 0 1
#> 113.1 22.86 1 34 0 0
#> 8 18.43 1 32 0 0
#> 187 9.92 1 39 1 0
#> 158 20.14 1 74 1 0
#> 149.1 8.37 1 33 1 0
#> 155 13.08 1 26 0 0
#> 175 21.91 1 43 0 0
#> 92 22.92 1 47 0 1
#> 18 15.21 1 49 1 0
#> 96 14.54 1 33 0 1
#> 150.1 20.33 1 48 0 0
#> 50 10.02 1 NA 1 0
#> 100 16.07 1 60 0 0
#> 52.1 10.42 1 52 0 1
#> 155.1 13.08 1 26 0 0
#> 32 20.90 1 37 1 0
#> 41.3 18.02 1 40 1 0
#> 199.1 19.81 1 NA 0 1
#> 42 12.43 1 49 0 1
#> 194 22.40 1 38 0 1
#> 63 22.77 1 31 1 0
#> 110.2 17.56 1 65 0 1
#> 199.2 19.81 1 NA 0 1
#> 78 23.88 1 43 0 0
#> 130.1 16.47 1 53 0 1
#> 159 10.55 1 50 0 1
#> 159.1 10.55 1 50 0 1
#> 184 17.77 1 38 0 0
#> 77.1 7.27 1 67 0 1
#> 30.1 17.43 1 78 0 0
#> 179 18.63 1 42 0 0
#> 150.2 20.33 1 48 0 0
#> 61 10.12 1 36 0 1
#> 175.1 21.91 1 43 0 0
#> 177 12.53 1 75 0 0
#> 13 14.34 1 54 0 1
#> 26.1 15.77 1 49 0 1
#> 36 21.19 1 48 0 1
#> 106 16.67 1 49 1 0
#> 93.1 10.33 1 52 0 1
#> 42.1 12.43 1 49 0 1
#> 52.2 10.42 1 52 0 1
#> 26.2 15.77 1 49 0 1
#> 179.1 18.63 1 42 0 0
#> 70 7.38 1 30 1 0
#> 168 23.72 1 70 0 0
#> 18.1 15.21 1 49 1 0
#> 51.1 18.23 1 83 0 1
#> 164 23.60 1 76 0 1
#> 8.1 18.43 1 32 0 0
#> 63.1 22.77 1 31 1 0
#> 110.3 17.56 1 65 0 1
#> 111.1 17.45 1 47 0 1
#> 187.1 9.92 1 39 1 0
#> 187.2 9.92 1 39 1 0
#> 130.2 16.47 1 53 0 1
#> 6 15.64 1 39 0 0
#> 168.1 23.72 1 70 0 0
#> 106.1 16.67 1 49 1 0
#> 155.2 13.08 1 26 0 0
#> 92.1 22.92 1 47 0 1
#> 85.2 16.44 1 36 0 0
#> 63.2 22.77 1 31 1 0
#> 170.1 19.54 1 43 0 1
#> 187.3 9.92 1 39 1 0
#> 147 24.00 0 76 1 0
#> 116 24.00 0 58 0 1
#> 142 24.00 0 53 0 0
#> 95 24.00 0 68 0 1
#> 1 24.00 0 23 1 0
#> 11 24.00 0 42 0 1
#> 138 24.00 0 44 1 0
#> 104 24.00 0 50 1 0
#> 138.1 24.00 0 44 1 0
#> 186 24.00 0 45 1 0
#> 44 24.00 0 56 0 0
#> 147.1 24.00 0 76 1 0
#> 156 24.00 0 50 1 0
#> 174 24.00 0 49 1 0
#> 138.2 24.00 0 44 1 0
#> 95.1 24.00 0 68 0 1
#> 135 24.00 0 58 1 0
#> 176 24.00 0 43 0 1
#> 47 24.00 0 38 0 1
#> 19 24.00 0 57 0 1
#> 28 24.00 0 67 1 0
#> 75 24.00 0 21 1 0
#> 94 24.00 0 51 0 1
#> 80 24.00 0 41 0 0
#> 137 24.00 0 45 1 0
#> 165 24.00 0 47 0 0
#> 143 24.00 0 51 0 0
#> 46 24.00 0 71 0 0
#> 126 24.00 0 48 0 0
#> 163 24.00 0 66 0 0
#> 135.1 24.00 0 58 1 0
#> 182 24.00 0 35 0 0
#> 2 24.00 0 9 0 0
#> 9 24.00 0 31 1 0
#> 182.1 24.00 0 35 0 0
#> 146 24.00 0 63 1 0
#> 115 24.00 0 NA 1 0
#> 193 24.00 0 45 0 1
#> 176.1 24.00 0 43 0 1
#> 173 24.00 0 19 0 1
#> 182.2 24.00 0 35 0 0
#> 75.1 24.00 0 21 1 0
#> 65 24.00 0 57 1 0
#> 84 24.00 0 39 0 1
#> 54 24.00 0 53 1 0
#> 19.1 24.00 0 57 0 1
#> 2.1 24.00 0 9 0 0
#> 67 24.00 0 25 0 0
#> 7 24.00 0 37 1 0
#> 7.1 24.00 0 37 1 0
#> 95.2 24.00 0 68 0 1
#> 73 24.00 0 NA 0 1
#> 148 24.00 0 61 1 0
#> 64 24.00 0 43 0 0
#> 44.1 24.00 0 56 0 0
#> 173.1 24.00 0 19 0 1
#> 75.2 24.00 0 21 1 0
#> 28.1 24.00 0 67 1 0
#> 28.2 24.00 0 67 1 0
#> 84.1 24.00 0 39 0 1
#> 137.1 24.00 0 45 1 0
#> 200 24.00 0 64 0 0
#> 172 24.00 0 41 0 0
#> 87 24.00 0 27 0 0
#> 20 24.00 0 46 1 0
#> 146.1 24.00 0 63 1 0
#> 27 24.00 0 63 1 0
#> 118 24.00 0 44 1 0
#> 27.1 24.00 0 63 1 0
#> 54.1 24.00 0 53 1 0
#> 34 24.00 0 36 0 0
#> 11.1 24.00 0 42 0 1
#> 46.1 24.00 0 71 0 0
#> 28.3 24.00 0 67 1 0
#> 53 24.00 0 32 0 1
#> 138.3 24.00 0 44 1 0
#> 163.1 24.00 0 66 0 0
#> 19.2 24.00 0 57 0 1
#> 151 24.00 0 42 0 0
#> 148.1 24.00 0 61 1 0
#> 142.1 24.00 0 53 0 0
#> 148.2 24.00 0 61 1 0
#> 116.1 24.00 0 58 0 1
#> 72 24.00 0 40 0 1
#> 174.1 24.00 0 49 1 0
#> 75.3 24.00 0 21 1 0
#> 47.1 24.00 0 38 0 1
#> 200.1 24.00 0 64 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.606 NA NA NA
#> 2 age, Cure model -0.00723 NA NA NA
#> 3 grade_ii, Cure model -0.601 NA NA NA
#> 4 grade_iii, Cure model 0.448 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00395 NA NA NA
#> 2 grade_ii, Survival model 0.310 NA NA NA
#> 3 grade_iii, Survival model 0.467 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.606067 -0.007235 -0.601123 0.448020
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 262.9
#> Residual Deviance: 253.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.606066809 -0.007234769 -0.601123361 0.448020075
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.00395153 0.30958035 0.46726968
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.675625737 0.419161040 0.567264355 0.083594444 0.215676532 0.774495727
#> [7] 0.854382730 0.059046246 0.949043061 0.419161040 0.880585706 0.419161040
#> [13] 0.576513620 0.702654763 0.828164918 0.991521531 0.475438693 0.639725329
#> [19] 0.245242507 0.125767600 0.322432767 0.702654763 0.923334163 0.530279331
#> [25] 0.765484360 0.225882616 0.475438693 0.351394887 0.264691373 0.974601234
#> [31] 0.399863830 0.332313630 0.456322751 0.974601234 0.185545937 0.274328474
#> [37] 0.511918781 0.603443775 0.966066266 0.284019940 0.603443775 0.059046246
#> [43] 0.083594444 0.125767600 0.380426634 0.889280872 0.312603962 0.923334163
#> [49] 0.738722013 0.195658196 0.105356985 0.684694813 0.720692882 0.284019940
#> [55] 0.630534417 0.828164918 0.738722013 0.254999821 0.419161040 0.792561887
#> [61] 0.175536861 0.146610139 0.475438693 0.005832824 0.576513620 0.810423914
#> [67] 0.810423914 0.465867049 0.949043061 0.530279331 0.361106875 0.284019940
#> [73] 0.871844466 0.195658196 0.783515451 0.729723540 0.639725329 0.225882616
#> [79] 0.548810115 0.854382730 0.792561887 0.828164918 0.639725329 0.361106875
#> [85] 0.940458224 0.019081253 0.684694813 0.399863830 0.044522993 0.380426634
#> [91] 0.146610139 0.475438693 0.511918781 0.889280872 0.889280872 0.576513620
#> [97] 0.666545413 0.019081253 0.548810115 0.738722013 0.105356985 0.603443775
#> [103] 0.146610139 0.332313630 0.889280872 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 167 41 171 69 153 14 93 129 77 41.1 101 41.2 130
#> 15.55 18.02 16.57 23.23 21.33 12.89 10.33 23.41 7.27 18.02 9.97 18.02 16.47
#> 157 52 127 110 26 90 113 166 157.1 149 30 123 99
#> 15.10 10.42 3.53 17.56 15.77 20.94 22.86 19.98 15.10 8.37 17.43 13.00 21.19
#> 110.1 58 190 91 51 170 40 91.1 66 68 111 85 25
#> 17.56 19.34 20.81 5.33 18.23 19.54 18.00 5.33 22.13 20.62 17.45 16.44 6.32
#> 150 85.1 129.1 69.1 113.1 8 187 158 149.1 155 175 92 18
#> 20.33 16.44 23.41 23.23 22.86 18.43 9.92 20.14 8.37 13.08 21.91 22.92 15.21
#> 96 150.1 100 52.1 155.1 32 41.3 42 194 63 110.2 78 130.1
#> 14.54 20.33 16.07 10.42 13.08 20.90 18.02 12.43 22.40 22.77 17.56 23.88 16.47
#> 159 159.1 184 77.1 30.1 179 150.2 61 175.1 177 13 26.1 36
#> 10.55 10.55 17.77 7.27 17.43 18.63 20.33 10.12 21.91 12.53 14.34 15.77 21.19
#> 106 93.1 42.1 52.2 26.2 179.1 70 168 18.1 51.1 164 8.1 63.1
#> 16.67 10.33 12.43 10.42 15.77 18.63 7.38 23.72 15.21 18.23 23.60 18.43 22.77
#> 110.3 111.1 187.1 187.2 130.2 6 168.1 106.1 155.2 92.1 85.2 63.2 170.1
#> 17.56 17.45 9.92 9.92 16.47 15.64 23.72 16.67 13.08 22.92 16.44 22.77 19.54
#> 187.3 147 116 142 95 1 11 138 104 138.1 186 44 147.1
#> 9.92 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156 174 138.2 95.1 135 176 47 19 28 75 94 80 137
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165 143 46 126 163 135.1 182 2 9 182.1 146 193 176.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 173 182.2 75.1 65 84 54 19.1 2.1 67 7 7.1 95.2 148
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64 44.1 173.1 75.2 28.1 28.2 84.1 137.1 200 172 87 20 146.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 27 118 27.1 54.1 34 11.1 46.1 28.3 53 138.3 163.1 19.2 151
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148.1 142.1 148.2 116.1 72 174.1 75.3 47.1 200.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[90]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01353972 0.54642035 0.33046771
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.46860871 0.01412655 -0.42039118
#> grade_iii, Cure model
#> 0.52236946
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 189 10.51 1 NA 1 0
#> 171 16.57 1 41 0 1
#> 51 18.23 1 83 0 1
#> 194 22.40 1 38 0 1
#> 154 12.63 1 20 1 0
#> 197 21.60 1 69 1 0
#> 188 16.16 1 46 0 1
#> 136 21.83 1 43 0 1
#> 167 15.55 1 56 1 0
#> 78 23.88 1 43 0 0
#> 29 15.45 1 68 1 0
#> 184 17.77 1 38 0 0
#> 130 16.47 1 53 0 1
#> 110 17.56 1 65 0 1
#> 168 23.72 1 70 0 0
#> 16 8.71 1 71 0 1
#> 133 14.65 1 57 0 0
#> 5 16.43 1 51 0 1
#> 40 18.00 1 28 1 0
#> 117 17.46 1 26 0 1
#> 195 11.76 1 NA 1 0
#> 8 18.43 1 32 0 0
#> 195.1 11.76 1 NA 1 0
#> 23 16.92 1 61 0 0
#> 69 23.23 1 25 0 1
#> 85 16.44 1 36 0 0
#> 168.1 23.72 1 70 0 0
#> 39 15.59 1 37 0 1
#> 169 22.41 1 46 0 0
#> 129 23.41 1 53 1 0
#> 184.1 17.77 1 38 0 0
#> 106 16.67 1 49 1 0
#> 85.1 16.44 1 36 0 0
#> 133.1 14.65 1 57 0 0
#> 168.2 23.72 1 70 0 0
#> 133.2 14.65 1 57 0 0
#> 183 9.24 1 67 1 0
#> 37 12.52 1 57 1 0
#> 39.1 15.59 1 37 0 1
#> 89 11.44 1 NA 0 0
#> 88 18.37 1 47 0 0
#> 18 15.21 1 49 1 0
#> 78.1 23.88 1 43 0 0
#> 128 20.35 1 35 0 1
#> 197.1 21.60 1 69 1 0
#> 88.1 18.37 1 47 0 0
#> 134 17.81 1 47 1 0
#> 55 19.34 1 69 0 1
#> 66 22.13 1 53 0 0
#> 37.1 12.52 1 57 1 0
#> 129.1 23.41 1 53 1 0
#> 150 20.33 1 48 0 0
#> 154.1 12.63 1 20 1 0
#> 139 21.49 1 63 1 0
#> 194.1 22.40 1 38 0 1
#> 157 15.10 1 47 0 0
#> 26 15.77 1 49 0 1
#> 127 3.53 1 62 0 1
#> 40.1 18.00 1 28 1 0
#> 4 17.64 1 NA 0 1
#> 96 14.54 1 33 0 1
#> 14 12.89 1 21 0 0
#> 29.1 15.45 1 68 1 0
#> 154.2 12.63 1 20 1 0
#> 187 9.92 1 39 1 0
#> 77 7.27 1 67 0 1
#> 57 14.46 1 45 0 1
#> 167.1 15.55 1 56 1 0
#> 130.1 16.47 1 53 0 1
#> 125 15.65 1 67 1 0
#> 63 22.77 1 31 1 0
#> 157.1 15.10 1 47 0 0
#> 76 19.22 1 54 0 1
#> 133.3 14.65 1 57 0 0
#> 111 17.45 1 47 0 1
#> 81 14.06 1 34 0 0
#> 96.1 14.54 1 33 0 1
#> 61 10.12 1 36 0 1
#> 4.1 17.64 1 NA 0 1
#> 107 11.18 1 54 1 0
#> 86 23.81 1 58 0 1
#> 76.1 19.22 1 54 0 1
#> 79 16.23 1 54 1 0
#> 129.2 23.41 1 53 1 0
#> 150.1 20.33 1 48 0 0
#> 70 7.38 1 30 1 0
#> 6 15.64 1 39 0 0
#> 133.4 14.65 1 57 0 0
#> 170 19.54 1 43 0 1
#> 55.1 19.34 1 69 0 1
#> 105 19.75 1 60 0 0
#> 175 21.91 1 43 0 0
#> 113 22.86 1 34 0 0
#> 169.1 22.41 1 46 0 0
#> 113.1 22.86 1 34 0 0
#> 61.1 10.12 1 36 0 1
#> 166 19.98 1 48 0 0
#> 10 10.53 1 34 0 0
#> 157.2 15.10 1 47 0 0
#> 187.1 9.92 1 39 1 0
#> 117.1 17.46 1 26 0 1
#> 96.2 14.54 1 33 0 1
#> 86.1 23.81 1 58 0 1
#> 105.1 19.75 1 60 0 0
#> 164 23.60 1 76 0 1
#> 133.5 14.65 1 57 0 0
#> 189.1 10.51 1 NA 1 0
#> 55.2 19.34 1 69 0 1
#> 39.2 15.59 1 37 0 1
#> 61.2 10.12 1 36 0 1
#> 5.1 16.43 1 51 0 1
#> 199 19.81 1 NA 0 1
#> 64 24.00 0 43 0 0
#> 27 24.00 0 63 1 0
#> 176 24.00 0 43 0 1
#> 1 24.00 0 23 1 0
#> 109 24.00 0 48 0 0
#> 1.1 24.00 0 23 1 0
#> 7 24.00 0 37 1 0
#> 84 24.00 0 39 0 1
#> 119 24.00 0 17 0 0
#> 83 24.00 0 6 0 0
#> 73 24.00 0 NA 0 1
#> 87 24.00 0 27 0 0
#> 160 24.00 0 31 1 0
#> 147 24.00 0 76 1 0
#> 73.1 24.00 0 NA 0 1
#> 178 24.00 0 52 1 0
#> 172 24.00 0 41 0 0
#> 198 24.00 0 66 0 1
#> 72 24.00 0 40 0 1
#> 137 24.00 0 45 1 0
#> 185 24.00 0 44 1 0
#> 17 24.00 0 38 0 1
#> 163 24.00 0 66 0 0
#> 22 24.00 0 52 1 0
#> 65 24.00 0 57 1 0
#> 17.1 24.00 0 38 0 1
#> 46 24.00 0 71 0 0
#> 75 24.00 0 21 1 0
#> 9 24.00 0 31 1 0
#> 83.1 24.00 0 6 0 0
#> 137.1 24.00 0 45 1 0
#> 46.1 24.00 0 71 0 0
#> 84.1 24.00 0 39 0 1
#> 174 24.00 0 49 1 0
#> 147.1 24.00 0 76 1 0
#> 17.2 24.00 0 38 0 1
#> 121 24.00 0 57 1 0
#> 137.2 24.00 0 45 1 0
#> 53 24.00 0 32 0 1
#> 121.1 24.00 0 57 1 0
#> 112 24.00 0 61 0 0
#> 142 24.00 0 53 0 0
#> 3 24.00 0 31 1 0
#> 20 24.00 0 46 1 0
#> 47 24.00 0 38 0 1
#> 44 24.00 0 56 0 0
#> 103 24.00 0 56 1 0
#> 132 24.00 0 55 0 0
#> 19 24.00 0 57 0 1
#> 3.1 24.00 0 31 1 0
#> 132.1 24.00 0 55 0 0
#> 191 24.00 0 60 0 1
#> 67 24.00 0 25 0 0
#> 147.2 24.00 0 76 1 0
#> 80 24.00 0 41 0 0
#> 19.1 24.00 0 57 0 1
#> 48 24.00 0 31 1 0
#> 198.1 24.00 0 66 0 1
#> 1.2 24.00 0 23 1 0
#> 119.1 24.00 0 17 0 0
#> 20.1 24.00 0 46 1 0
#> 146 24.00 0 63 1 0
#> 198.2 24.00 0 66 0 1
#> 137.3 24.00 0 45 1 0
#> 104 24.00 0 50 1 0
#> 173 24.00 0 19 0 1
#> 132.2 24.00 0 55 0 0
#> 84.2 24.00 0 39 0 1
#> 12 24.00 0 63 0 0
#> 34 24.00 0 36 0 0
#> 126 24.00 0 48 0 0
#> 143 24.00 0 51 0 0
#> 74 24.00 0 43 0 1
#> 73.2 24.00 0 NA 0 1
#> 20.2 24.00 0 46 1 0
#> 80.1 24.00 0 41 0 0
#> 33 24.00 0 53 0 0
#> 33.1 24.00 0 53 0 0
#> 28 24.00 0 67 1 0
#> 1.3 24.00 0 23 1 0
#> 67.1 24.00 0 25 0 0
#> 196 24.00 0 19 0 0
#> 185.1 24.00 0 44 1 0
#> 64.1 24.00 0 43 0 0
#> 48.1 24.00 0 31 1 0
#> 191.1 24.00 0 60 0 1
#> 46.2 24.00 0 71 0 0
#> 34.1 24.00 0 36 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.469 NA NA NA
#> 2 age, Cure model 0.0141 NA NA NA
#> 3 grade_ii, Cure model -0.420 NA NA NA
#> 4 grade_iii, Cure model 0.522 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0135 NA NA NA
#> 2 grade_ii, Survival model 0.546 NA NA NA
#> 3 grade_iii, Survival model 0.330 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.46861 0.01413 -0.42039 0.52237
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.1
#> Residual Deviance: 251.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.46860871 0.01412655 -0.42039118 0.52236946
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01353972 0.54642035 0.33046771
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.3690824000 0.2496859684 0.0704262775 0.7785302273 0.1024586821
#> [6] 0.4549487293 0.0956418067 0.5339020737 0.0005698114 0.5568935743
#> [11] 0.2883236767 0.3795594933 0.3079782664 0.0078900907 0.9466787222
#> [16] 0.6276355684 0.4220600388 0.2595326017 0.3181064826 0.2214930345
#> [21] 0.3482805796 0.0371250327 0.4005922596 0.0078900907 0.5000640612
#> [26] 0.0587535138 0.0235231614 0.2883236767 0.3586648255 0.4005922596
#> [31] 0.6276355684 0.0078900907 0.6276355684 0.9334723872 0.8166081606
#> [36] 0.5000640612 0.2307811473 0.5801853999 0.0005698114 0.1234171589
#> [41] 0.1024586821 0.2307811473 0.2785946313 0.1780011151 0.0824376275
#> [46] 0.8166081606 0.0235231614 0.1306818645 0.7785302273 0.1162092475
#> [51] 0.0704262775 0.5919770167 0.4661030558 0.9865824339 0.2595326017
#> [56] 0.7013048402 0.7654180356 0.5568935743 0.7785302273 0.9073576487
#> [61] 0.9732372678 0.7393874428 0.5339020737 0.3795594933 0.4773335072
#> [66] 0.0531430302 0.5919770167 0.2035650493 0.6276355684 0.3380675294
#> [71] 0.7523612038 0.7013048402 0.8684482284 0.8423577701 0.0034128106
#> [76] 0.2035650493 0.4438633114 0.0235231614 0.1306818645 0.9599718195
#> [81] 0.4886445593 0.6276355684 0.1696124267 0.1780011151 0.1534237326
#> [86] 0.0889315282 0.0423704941 0.0587535138 0.0423704941 0.8684482284
#> [91] 0.1455777731 0.8553662976 0.5919770167 0.9073576487 0.3181064826
#> [96] 0.7013048402 0.0034128106 0.1534237326 0.0183726055 0.6276355684
#> [101] 0.1780011151 0.5000640612 0.8684482284 0.4220600388 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#>
#> $Time
#> 171 51 194 154 197 188 136 167 78 29 184 130 110
#> 16.57 18.23 22.40 12.63 21.60 16.16 21.83 15.55 23.88 15.45 17.77 16.47 17.56
#> 168 16 133 5 40 117 8 23 69 85 168.1 39 169
#> 23.72 8.71 14.65 16.43 18.00 17.46 18.43 16.92 23.23 16.44 23.72 15.59 22.41
#> 129 184.1 106 85.1 133.1 168.2 133.2 183 37 39.1 88 18 78.1
#> 23.41 17.77 16.67 16.44 14.65 23.72 14.65 9.24 12.52 15.59 18.37 15.21 23.88
#> 128 197.1 88.1 134 55 66 37.1 129.1 150 154.1 139 194.1 157
#> 20.35 21.60 18.37 17.81 19.34 22.13 12.52 23.41 20.33 12.63 21.49 22.40 15.10
#> 26 127 40.1 96 14 29.1 154.2 187 77 57 167.1 130.1 125
#> 15.77 3.53 18.00 14.54 12.89 15.45 12.63 9.92 7.27 14.46 15.55 16.47 15.65
#> 63 157.1 76 133.3 111 81 96.1 61 107 86 76.1 79 129.2
#> 22.77 15.10 19.22 14.65 17.45 14.06 14.54 10.12 11.18 23.81 19.22 16.23 23.41
#> 150.1 70 6 133.4 170 55.1 105 175 113 169.1 113.1 61.1 166
#> 20.33 7.38 15.64 14.65 19.54 19.34 19.75 21.91 22.86 22.41 22.86 10.12 19.98
#> 10 157.2 187.1 117.1 96.2 86.1 105.1 164 133.5 55.2 39.2 61.2 5.1
#> 10.53 15.10 9.92 17.46 14.54 23.81 19.75 23.60 14.65 19.34 15.59 10.12 16.43
#> 64 27 176 1 109 1.1 7 84 119 83 87 160 147
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178 172 198 72 137 185 17 163 22 65 17.1 46 75
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9 83.1 137.1 46.1 84.1 174 147.1 17.2 121 137.2 53 121.1 112
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142 3 20 47 44 103 132 19 3.1 132.1 191 67 147.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80 19.1 48 198.1 1.2 119.1 20.1 146 198.2 137.3 104 173 132.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 84.2 12 34 126 143 74 20.2 80.1 33 33.1 28 1.3 67.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 196 185.1 64.1 48.1 191.1 46.2 34.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[91]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -4.276512e-05 5.918900e-01 2.840875e-01
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.31301294 0.01902852 0.52299719
#> grade_iii, Cure model
#> 1.03995455
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 133 14.65 1 57 0 0
#> 55 19.34 1 69 0 1
#> 24 23.89 1 38 0 0
#> 77 7.27 1 67 0 1
#> 97 19.14 1 65 0 1
#> 114 13.68 1 NA 0 0
#> 117 17.46 1 26 0 1
#> 105 19.75 1 60 0 0
#> 24.1 23.89 1 38 0 0
#> 189 10.51 1 NA 1 0
#> 89 11.44 1 NA 0 0
#> 106 16.67 1 49 1 0
#> 37 12.52 1 57 1 0
#> 15 22.68 1 48 0 0
#> 68 20.62 1 44 0 0
#> 166 19.98 1 48 0 0
#> 37.1 12.52 1 57 1 0
#> 117.1 17.46 1 26 0 1
#> 16 8.71 1 71 0 1
#> 110 17.56 1 65 0 1
#> 190 20.81 1 42 1 0
#> 18 15.21 1 49 1 0
#> 189.1 10.51 1 NA 1 0
#> 184 17.77 1 38 0 0
#> 57 14.46 1 45 0 1
#> 41 18.02 1 40 1 0
#> 129 23.41 1 53 1 0
#> 57.1 14.46 1 45 0 1
#> 129.1 23.41 1 53 1 0
#> 88 18.37 1 47 0 0
#> 101 9.97 1 10 0 1
#> 59 10.16 1 NA 1 0
#> 106.1 16.67 1 49 1 0
#> 189.2 10.51 1 NA 1 0
#> 164 23.60 1 76 0 1
#> 52 10.42 1 52 0 1
#> 66 22.13 1 53 0 0
#> 18.1 15.21 1 49 1 0
#> 139 21.49 1 63 1 0
#> 150 20.33 1 48 0 0
#> 39 15.59 1 37 0 1
#> 39.1 15.59 1 37 0 1
#> 127 3.53 1 62 0 1
#> 111 17.45 1 47 0 1
#> 43 12.10 1 61 0 1
#> 18.2 15.21 1 49 1 0
#> 39.2 15.59 1 37 0 1
#> 125 15.65 1 67 1 0
#> 188 16.16 1 46 0 1
#> 167 15.55 1 56 1 0
#> 37.2 12.52 1 57 1 0
#> 58 19.34 1 39 0 0
#> 79 16.23 1 54 1 0
#> 107 11.18 1 54 1 0
#> 107.1 11.18 1 54 1 0
#> 13 14.34 1 54 0 1
#> 30 17.43 1 78 0 0
#> 194 22.40 1 38 0 1
#> 8 18.43 1 32 0 0
#> 51 18.23 1 83 0 1
#> 39.3 15.59 1 37 0 1
#> 194.1 22.40 1 38 0 1
#> 117.2 17.46 1 26 0 1
#> 181 16.46 1 45 0 1
#> 26 15.77 1 49 0 1
#> 123 13.00 1 44 1 0
#> 86 23.81 1 58 0 1
#> 49 12.19 1 48 1 0
#> 177 12.53 1 75 0 0
#> 150.1 20.33 1 48 0 0
#> 97.1 19.14 1 65 0 1
#> 63 22.77 1 31 1 0
#> 29 15.45 1 68 1 0
#> 39.4 15.59 1 37 0 1
#> 90 20.94 1 50 0 1
#> 179 18.63 1 42 0 0
#> 30.1 17.43 1 78 0 0
#> 125.1 15.65 1 67 1 0
#> 91 5.33 1 61 0 1
#> 106.2 16.67 1 49 1 0
#> 153 21.33 1 55 1 0
#> 89.1 11.44 1 NA 0 0
#> 41.1 18.02 1 40 1 0
#> 150.2 20.33 1 48 0 0
#> 10 10.53 1 34 0 0
#> 107.2 11.18 1 54 1 0
#> 154 12.63 1 20 1 0
#> 187 9.92 1 39 1 0
#> 23 16.92 1 61 0 0
#> 157 15.10 1 47 0 0
#> 177.1 12.53 1 75 0 0
#> 4 17.64 1 NA 0 1
#> 69 23.23 1 25 0 1
#> 155 13.08 1 26 0 0
#> 45 17.42 1 54 0 1
#> 134 17.81 1 47 1 0
#> 89.2 11.44 1 NA 0 0
#> 76 19.22 1 54 0 1
#> 125.2 15.65 1 67 1 0
#> 124 9.73 1 NA 1 0
#> 57.2 14.46 1 45 0 1
#> 127.1 3.53 1 62 0 1
#> 51.1 18.23 1 83 0 1
#> 164.1 23.60 1 76 0 1
#> 51.2 18.23 1 83 0 1
#> 55.1 19.34 1 69 0 1
#> 51.3 18.23 1 83 0 1
#> 76.1 19.22 1 54 0 1
#> 86.1 23.81 1 58 0 1
#> 37.3 12.52 1 57 1 0
#> 85 16.44 1 36 0 0
#> 114.1 13.68 1 NA 0 0
#> 3 24.00 0 31 1 0
#> 156 24.00 0 50 1 0
#> 12 24.00 0 63 0 0
#> 83 24.00 0 6 0 0
#> 62 24.00 0 71 0 0
#> 54 24.00 0 53 1 0
#> 2 24.00 0 9 0 0
#> 103 24.00 0 56 1 0
#> 17 24.00 0 38 0 1
#> 54.1 24.00 0 53 1 0
#> 131 24.00 0 66 0 0
#> 1 24.00 0 23 1 0
#> 144 24.00 0 28 0 1
#> 75 24.00 0 21 1 0
#> 120 24.00 0 68 0 1
#> 20 24.00 0 46 1 0
#> 33 24.00 0 53 0 0
#> 142 24.00 0 53 0 0
#> 20.1 24.00 0 46 1 0
#> 178 24.00 0 52 1 0
#> 27 24.00 0 63 1 0
#> 191 24.00 0 60 0 1
#> 191.1 24.00 0 60 0 1
#> 11 24.00 0 42 0 1
#> 135 24.00 0 58 1 0
#> 11.1 24.00 0 42 0 1
#> 64 24.00 0 43 0 0
#> 3.1 24.00 0 31 1 0
#> 94 24.00 0 51 0 1
#> 1.1 24.00 0 23 1 0
#> 185 24.00 0 44 1 0
#> 200 24.00 0 64 0 0
#> 11.2 24.00 0 42 0 1
#> 119 24.00 0 17 0 0
#> 178.1 24.00 0 52 1 0
#> 82 24.00 0 34 0 0
#> 116 24.00 0 58 0 1
#> 84 24.00 0 39 0 1
#> 151 24.00 0 42 0 0
#> 165 24.00 0 47 0 0
#> 186 24.00 0 45 1 0
#> 102 24.00 0 49 0 0
#> 118 24.00 0 44 1 0
#> 165.1 24.00 0 47 0 0
#> 74 24.00 0 43 0 1
#> 1.2 24.00 0 23 1 0
#> 1.3 24.00 0 23 1 0
#> 109 24.00 0 48 0 0
#> 62.1 24.00 0 71 0 0
#> 178.2 24.00 0 52 1 0
#> 64.1 24.00 0 43 0 0
#> 120.1 24.00 0 68 0 1
#> 95 24.00 0 68 0 1
#> 126 24.00 0 48 0 0
#> 161 24.00 0 45 0 0
#> 132 24.00 0 55 0 0
#> 143 24.00 0 51 0 0
#> 161.1 24.00 0 45 0 0
#> 193 24.00 0 45 0 1
#> 198 24.00 0 66 0 1
#> 53 24.00 0 32 0 1
#> 118.1 24.00 0 44 1 0
#> 161.2 24.00 0 45 0 0
#> 80 24.00 0 41 0 0
#> 146 24.00 0 63 1 0
#> 22 24.00 0 52 1 0
#> 87 24.00 0 27 0 0
#> 182 24.00 0 35 0 0
#> 146.1 24.00 0 63 1 0
#> 115 24.00 0 NA 1 0
#> 200.1 24.00 0 64 0 0
#> 121 24.00 0 57 1 0
#> 173 24.00 0 19 0 1
#> 44 24.00 0 56 0 0
#> 47 24.00 0 38 0 1
#> 122 24.00 0 66 0 0
#> 2.1 24.00 0 9 0 0
#> 80.1 24.00 0 41 0 0
#> 44.1 24.00 0 56 0 0
#> 165.2 24.00 0 47 0 0
#> 120.2 24.00 0 68 0 1
#> 44.2 24.00 0 56 0 0
#> 46 24.00 0 71 0 0
#> 74.1 24.00 0 43 0 1
#> 102.1 24.00 0 49 0 0
#> 22.1 24.00 0 52 1 0
#> 65 24.00 0 57 1 0
#> 116.1 24.00 0 58 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.31 NA NA NA
#> 2 age, Cure model 0.0190 NA NA NA
#> 3 grade_ii, Cure model 0.523 NA NA NA
#> 4 grade_iii, Cure model 1.04 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0000428 NA NA NA
#> 2 grade_ii, Survival model 0.592 NA NA NA
#> 3 grade_iii, Survival model 0.284 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.31301 0.01903 0.52300 1.03995
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 259.6
#> Residual Deviance: 247.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.31301294 0.01902852 0.52299719 1.03995455
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -4.276512e-05 5.918900e-01 2.840875e-01
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.79289109 0.34810427 0.02445470 0.97169411 0.39986608 0.53724714
#> [7] 0.33719483 0.02445470 0.61051972 0.87007095 0.18855892 0.28369962
#> [13] 0.32628633 0.87007095 0.53724714 0.96455885 0.52780211 0.27275519
#> [19] 0.76164711 0.51830186 0.80076137 0.48969534 0.13468538 0.80076137
#> [25] 0.13468538 0.44075335 0.95021076 0.61051972 0.10239206 0.94299718
#> [31] 0.22565832 0.76164711 0.23806570 0.29464491 0.70524756 0.70524756
#> [37] 0.98591388 0.56462341 0.90686487 0.76164711 0.70524756 0.68038842
#> [43] 0.66306015 0.74543004 0.87007095 0.34810427 0.65434061 0.91423827
#> [49] 0.91423827 0.82392054 0.57385102 0.20152900 0.43046811 0.45103909
#> [55] 0.70524756 0.20152900 0.53724714 0.63671303 0.67174249 0.83945919
#> [61] 0.06658297 0.89947193 0.85482700 0.29464491 0.39986608 0.17559103
#> [67] 0.75357357 0.70524756 0.26144594 0.42018322 0.57385102 0.68038842
#> [73] 0.97881239 0.61051972 0.24997519 0.48969534 0.29464491 0.93576559
#> [79] 0.91423827 0.84717118 0.95740643 0.60133961 0.78502100 0.85482700
#> [85] 0.16180437 0.83168983 0.59215986 0.50880190 0.37920826 0.68038842
#> [91] 0.80076137 0.98591388 0.45103909 0.10239206 0.45103909 0.34810427
#> [97] 0.45103909 0.37920826 0.06658297 0.87007095 0.64552673 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000
#>
#> $Time
#> 133 55 24 77 97 117 105 24.1 106 37 15 68 166
#> 14.65 19.34 23.89 7.27 19.14 17.46 19.75 23.89 16.67 12.52 22.68 20.62 19.98
#> 37.1 117.1 16 110 190 18 184 57 41 129 57.1 129.1 88
#> 12.52 17.46 8.71 17.56 20.81 15.21 17.77 14.46 18.02 23.41 14.46 23.41 18.37
#> 101 106.1 164 52 66 18.1 139 150 39 39.1 127 111 43
#> 9.97 16.67 23.60 10.42 22.13 15.21 21.49 20.33 15.59 15.59 3.53 17.45 12.10
#> 18.2 39.2 125 188 167 37.2 58 79 107 107.1 13 30 194
#> 15.21 15.59 15.65 16.16 15.55 12.52 19.34 16.23 11.18 11.18 14.34 17.43 22.40
#> 8 51 39.3 194.1 117.2 181 26 123 86 49 177 150.1 97.1
#> 18.43 18.23 15.59 22.40 17.46 16.46 15.77 13.00 23.81 12.19 12.53 20.33 19.14
#> 63 29 39.4 90 179 30.1 125.1 91 106.2 153 41.1 150.2 10
#> 22.77 15.45 15.59 20.94 18.63 17.43 15.65 5.33 16.67 21.33 18.02 20.33 10.53
#> 107.2 154 187 23 157 177.1 69 155 45 134 76 125.2 57.2
#> 11.18 12.63 9.92 16.92 15.10 12.53 23.23 13.08 17.42 17.81 19.22 15.65 14.46
#> 127.1 51.1 164.1 51.2 55.1 51.3 76.1 86.1 37.3 85 3 156 12
#> 3.53 18.23 23.60 18.23 19.34 18.23 19.22 23.81 12.52 16.44 24.00 24.00 24.00
#> 83 62 54 2 103 17 54.1 131 1 144 75 120 20
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33 142 20.1 178 27 191 191.1 11 135 11.1 64 3.1 94
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1.1 185 200 11.2 119 178.1 82 116 84 151 165 186 102
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 118 165.1 74 1.2 1.3 109 62.1 178.2 64.1 120.1 95 126 161
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 132 143 161.1 193 198 53 118.1 161.2 80 146 22 87 182
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 146.1 200.1 121 173 44 47 122 2.1 80.1 44.1 165.2 120.2 44.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 46 74.1 102.1 22.1 65 116.1
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[92]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.007032618 0.171443590 0.324185319
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.03358013 0.02318742 -0.54568970
#> grade_iii, Cure model
#> 0.82876310
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 43 12.10 1 61 0 1
#> 105 19.75 1 60 0 0
#> 76 19.22 1 54 0 1
#> 86 23.81 1 58 0 1
#> 29 15.45 1 68 1 0
#> 99 21.19 1 38 0 1
#> 4 17.64 1 NA 0 1
#> 16 8.71 1 71 0 1
#> 25 6.32 1 34 1 0
#> 26 15.77 1 49 0 1
#> 166 19.98 1 48 0 0
#> 158 20.14 1 74 1 0
#> 134 17.81 1 47 1 0
#> 25.1 6.32 1 34 1 0
#> 76.1 19.22 1 54 0 1
#> 125 15.65 1 67 1 0
#> 23 16.92 1 61 0 0
#> 175 21.91 1 43 0 0
#> 177 12.53 1 75 0 0
#> 97 19.14 1 65 0 1
#> 97.1 19.14 1 65 0 1
#> 93 10.33 1 52 0 1
#> 50 10.02 1 NA 1 0
#> 184 17.77 1 38 0 0
#> 23.1 16.92 1 61 0 0
#> 157 15.10 1 47 0 0
#> 195 11.76 1 NA 1 0
#> 157.1 15.10 1 47 0 0
#> 175.1 21.91 1 43 0 0
#> 169 22.41 1 46 0 0
#> 50.1 10.02 1 NA 1 0
#> 168 23.72 1 70 0 0
#> 8 18.43 1 32 0 0
#> 199 19.81 1 NA 0 1
#> 69 23.23 1 25 0 1
#> 4.1 17.64 1 NA 0 1
#> 129 23.41 1 53 1 0
#> 195.1 11.76 1 NA 1 0
#> 107 11.18 1 54 1 0
#> 59 10.16 1 NA 1 0
#> 85 16.44 1 36 0 0
#> 23.2 16.92 1 61 0 0
#> 86.1 23.81 1 58 0 1
#> 69.1 23.23 1 25 0 1
#> 4.2 17.64 1 NA 0 1
#> 78 23.88 1 43 0 0
#> 58 19.34 1 39 0 0
#> 69.2 23.23 1 25 0 1
#> 16.1 8.71 1 71 0 1
#> 89 11.44 1 NA 0 0
#> 42 12.43 1 49 0 1
#> 61 10.12 1 36 0 1
#> 153 21.33 1 55 1 0
#> 39 15.59 1 37 0 1
#> 114 13.68 1 NA 0 0
#> 77 7.27 1 67 0 1
#> 29.1 15.45 1 68 1 0
#> 177.1 12.53 1 75 0 0
#> 32 20.90 1 37 1 0
#> 10 10.53 1 34 0 0
#> 90 20.94 1 50 0 1
#> 59.1 10.16 1 NA 1 0
#> 91 5.33 1 61 0 1
#> 183 9.24 1 67 1 0
#> 90.1 20.94 1 50 0 1
#> 78.1 23.88 1 43 0 0
#> 153.1 21.33 1 55 1 0
#> 166.1 19.98 1 48 0 0
#> 58.1 19.34 1 39 0 0
#> 25.2 6.32 1 34 1 0
#> 68 20.62 1 44 0 0
#> 14 12.89 1 21 0 0
#> 101 9.97 1 10 0 1
#> 52 10.42 1 52 0 1
#> 15 22.68 1 48 0 0
#> 145 10.07 1 65 1 0
#> 166.2 19.98 1 48 0 0
#> 77.1 7.27 1 67 0 1
#> 158.1 20.14 1 74 1 0
#> 56 12.21 1 60 0 0
#> 14.1 12.89 1 21 0 0
#> 195.2 11.76 1 NA 1 0
#> 50.2 10.02 1 NA 1 0
#> 108 18.29 1 39 0 1
#> 197 21.60 1 69 1 0
#> 180 14.82 1 37 0 0
#> 52.1 10.42 1 52 0 1
#> 184.1 17.77 1 38 0 0
#> 57 14.46 1 45 0 1
#> 130 16.47 1 53 0 1
#> 180.1 14.82 1 37 0 0
#> 16.2 8.71 1 71 0 1
#> 117 17.46 1 26 0 1
#> 113 22.86 1 34 0 0
#> 39.1 15.59 1 37 0 1
#> 113.1 22.86 1 34 0 0
#> 129.1 23.41 1 53 1 0
#> 39.2 15.59 1 37 0 1
#> 197.1 21.60 1 69 1 0
#> 107.1 11.18 1 54 1 0
#> 15.1 22.68 1 48 0 0
#> 56.1 12.21 1 60 0 0
#> 91.1 5.33 1 61 0 1
#> 4.3 17.64 1 NA 0 1
#> 192 16.44 1 31 1 0
#> 170 19.54 1 43 0 1
#> 170.1 19.54 1 43 0 1
#> 128 20.35 1 35 0 1
#> 130.1 16.47 1 53 0 1
#> 14.2 12.89 1 21 0 0
#> 85.1 16.44 1 36 0 0
#> 79 16.23 1 54 1 0
#> 12 24.00 0 63 0 0
#> 122 24.00 0 66 0 0
#> 17 24.00 0 38 0 1
#> 73 24.00 0 NA 0 1
#> 143 24.00 0 51 0 0
#> 87 24.00 0 27 0 0
#> 82 24.00 0 34 0 0
#> 142 24.00 0 53 0 0
#> 64 24.00 0 43 0 0
#> 152 24.00 0 36 0 1
#> 38 24.00 0 31 1 0
#> 185 24.00 0 44 1 0
#> 22 24.00 0 52 1 0
#> 75 24.00 0 21 1 0
#> 3 24.00 0 31 1 0
#> 82.1 24.00 0 34 0 0
#> 9 24.00 0 31 1 0
#> 160 24.00 0 31 1 0
#> 196 24.00 0 19 0 0
#> 172 24.00 0 41 0 0
#> 19 24.00 0 57 0 1
#> 135 24.00 0 58 1 0
#> 94 24.00 0 51 0 1
#> 46 24.00 0 71 0 0
#> 200 24.00 0 64 0 0
#> 173 24.00 0 19 0 1
#> 22.1 24.00 0 52 1 0
#> 95 24.00 0 68 0 1
#> 119 24.00 0 17 0 0
#> 44 24.00 0 56 0 0
#> 65 24.00 0 57 1 0
#> 119.1 24.00 0 17 0 0
#> 144 24.00 0 28 0 1
#> 186 24.00 0 45 1 0
#> 182 24.00 0 35 0 0
#> 172.1 24.00 0 41 0 0
#> 35 24.00 0 51 0 0
#> 54 24.00 0 53 1 0
#> 67 24.00 0 25 0 0
#> 137 24.00 0 45 1 0
#> 196.1 24.00 0 19 0 0
#> 162 24.00 0 51 0 0
#> 74 24.00 0 43 0 1
#> 38.1 24.00 0 31 1 0
#> 196.2 24.00 0 19 0 0
#> 103 24.00 0 56 1 0
#> 121 24.00 0 57 1 0
#> 71 24.00 0 51 0 0
#> 1 24.00 0 23 1 0
#> 151 24.00 0 42 0 0
#> 162.1 24.00 0 51 0 0
#> 121.1 24.00 0 57 1 0
#> 53 24.00 0 32 0 1
#> 115 24.00 0 NA 1 0
#> 118 24.00 0 44 1 0
#> 174 24.00 0 49 1 0
#> 83 24.00 0 6 0 0
#> 138 24.00 0 44 1 0
#> 109 24.00 0 48 0 0
#> 147 24.00 0 76 1 0
#> 112 24.00 0 61 0 0
#> 44.1 24.00 0 56 0 0
#> 94.1 24.00 0 51 0 1
#> 148 24.00 0 61 1 0
#> 44.2 24.00 0 56 0 0
#> 94.2 24.00 0 51 0 1
#> 94.3 24.00 0 51 0 1
#> 19.1 24.00 0 57 0 1
#> 109.1 24.00 0 48 0 0
#> 84 24.00 0 39 0 1
#> 38.2 24.00 0 31 1 0
#> 103.1 24.00 0 56 1 0
#> 176 24.00 0 43 0 1
#> 21 24.00 0 47 0 0
#> 132 24.00 0 55 0 0
#> 185.1 24.00 0 44 1 0
#> 21.1 24.00 0 47 0 0
#> 104 24.00 0 50 1 0
#> 53.1 24.00 0 32 0 1
#> 7 24.00 0 37 1 0
#> 22.2 24.00 0 52 1 0
#> 33 24.00 0 53 0 0
#> 102 24.00 0 49 0 0
#> 142.1 24.00 0 53 0 0
#> 103.2 24.00 0 56 1 0
#> 103.3 24.00 0 56 1 0
#> 148.1 24.00 0 61 1 0
#> 178 24.00 0 52 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.03 NA NA NA
#> 2 age, Cure model 0.0232 NA NA NA
#> 3 grade_ii, Cure model -0.546 NA NA NA
#> 4 grade_iii, Cure model 0.829 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00703 NA NA NA
#> 2 grade_ii, Survival model 0.171 NA NA NA
#> 3 grade_iii, Survival model 0.324 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.03358 0.02319 -0.54569 0.82876
#>
#> Degrees of Freedom: 182 Total (i.e. Null); 179 Residual
#> Null Deviance: 253
#> Residual Deviance: 237.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.03358013 0.02318742 -0.54568970 0.82876310
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.007032618 0.171443590 0.324185319
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.86499147 0.51728433 0.56405871 0.12263308 0.75831300 0.40341414
#> [7] 0.93828857 0.96952559 0.72081848 0.48843945 0.46853887 0.61629373
#> [13] 0.96952559 0.56405871 0.72853143 0.64975117 0.32975099 0.83013433
#> [19] 0.58189942 0.58189942 0.90549316 0.62475686 0.64975117 0.77288601
#> [25] 0.77288601 0.32975099 0.31608106 0.16410879 0.59911511 0.21823280
#> [31] 0.18459461 0.87186543 0.68971853 0.64975117 0.12263308 0.21823280
#> [37] 0.05856612 0.54562231 0.21823280 0.93828857 0.84417909 0.91212403
#> [43] 0.38015385 0.73617147 0.95712487 0.75831300 0.83013433 0.43654348
#> [49] 0.88540280 0.41494489 0.98788880 0.93179965 0.41494489 0.05856612
#> [55] 0.38015385 0.48843945 0.54562231 0.96952559 0.44733387 0.80890819
#> [61] 0.92526973 0.89218351 0.28889347 0.91871745 0.48843945 0.95712487
#> [67] 0.46853887 0.85117529 0.80890819 0.60775415 0.35577947 0.78735219
#> [73] 0.89218351 0.62475686 0.80173981 0.67390275 0.78735219 0.93828857
#> [79] 0.64143106 0.26064117 0.73617147 0.26064117 0.18459461 0.73617147
#> [85] 0.35577947 0.87186543 0.28889347 0.85117529 0.98788880 0.68971853
#> [91] 0.52698727 0.52698727 0.45803070 0.67390275 0.80890819 0.68971853
#> [97] 0.71302617 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 43 105 76 86 29 99 16 25 26 166 158 134 25.1
#> 12.10 19.75 19.22 23.81 15.45 21.19 8.71 6.32 15.77 19.98 20.14 17.81 6.32
#> 76.1 125 23 175 177 97 97.1 93 184 23.1 157 157.1 175.1
#> 19.22 15.65 16.92 21.91 12.53 19.14 19.14 10.33 17.77 16.92 15.10 15.10 21.91
#> 169 168 8 69 129 107 85 23.2 86.1 69.1 78 58 69.2
#> 22.41 23.72 18.43 23.23 23.41 11.18 16.44 16.92 23.81 23.23 23.88 19.34 23.23
#> 16.1 42 61 153 39 77 29.1 177.1 32 10 90 91 183
#> 8.71 12.43 10.12 21.33 15.59 7.27 15.45 12.53 20.90 10.53 20.94 5.33 9.24
#> 90.1 78.1 153.1 166.1 58.1 25.2 68 14 101 52 15 145 166.2
#> 20.94 23.88 21.33 19.98 19.34 6.32 20.62 12.89 9.97 10.42 22.68 10.07 19.98
#> 77.1 158.1 56 14.1 108 197 180 52.1 184.1 57 130 180.1 16.2
#> 7.27 20.14 12.21 12.89 18.29 21.60 14.82 10.42 17.77 14.46 16.47 14.82 8.71
#> 117 113 39.1 113.1 129.1 39.2 197.1 107.1 15.1 56.1 91.1 192 170
#> 17.46 22.86 15.59 22.86 23.41 15.59 21.60 11.18 22.68 12.21 5.33 16.44 19.54
#> 170.1 128 130.1 14.2 85.1 79 12 122 17 143 87 82 142
#> 19.54 20.35 16.47 12.89 16.44 16.23 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64 152 38 185 22 75 3 82.1 9 160 196 172 19
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135 94 46 200 173 22.1 95 119 44 65 119.1 144 186
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 182 172.1 35 54 67 137 196.1 162 74 38.1 196.2 103 121
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71 1 151 162.1 121.1 53 118 174 83 138 109 147 112
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44.1 94.1 148 44.2 94.2 94.3 19.1 109.1 84 38.2 103.1 176 21
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 132 185.1 21.1 104 53.1 7 22.2 33 102 142.1 103.2 103.3 148.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178
#> 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[93]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.01047868 0.85786753 0.40710294
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.60979397 0.01146743 0.08266473
#> grade_iii, Cure model
#> 0.65766125
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 49 12.19 1 48 1 0
#> 166 19.98 1 48 0 0
#> 26 15.77 1 49 0 1
#> 51 18.23 1 83 0 1
#> 63 22.77 1 31 1 0
#> 117 17.46 1 26 0 1
#> 16 8.71 1 71 0 1
#> 133 14.65 1 57 0 0
#> 32 20.90 1 37 1 0
#> 194 22.40 1 38 0 1
#> 37 12.52 1 57 1 0
#> 184 17.77 1 38 0 0
#> 91 5.33 1 61 0 1
#> 181 16.46 1 45 0 1
#> 10 10.53 1 34 0 0
#> 30 17.43 1 78 0 0
#> 26.1 15.77 1 49 0 1
#> 51.1 18.23 1 83 0 1
#> 92 22.92 1 47 0 1
#> 55 19.34 1 69 0 1
#> 145 10.07 1 65 1 0
#> 93 10.33 1 52 0 1
#> 42 12.43 1 49 0 1
#> 25 6.32 1 34 1 0
#> 45 17.42 1 54 0 1
#> 26.2 15.77 1 49 0 1
#> 81 14.06 1 34 0 0
#> 70 7.38 1 30 1 0
#> 114 13.68 1 NA 0 0
#> 190 20.81 1 42 1 0
#> 77 7.27 1 67 0 1
#> 56 12.21 1 60 0 0
#> 197 21.60 1 69 1 0
#> 123 13.00 1 44 1 0
#> 81.1 14.06 1 34 0 0
#> 58 19.34 1 39 0 0
#> 66 22.13 1 53 0 0
#> 43 12.10 1 61 0 1
#> 32.1 20.90 1 37 1 0
#> 136 21.83 1 43 0 1
#> 93.1 10.33 1 52 0 1
#> 66.1 22.13 1 53 0 0
#> 194.1 22.40 1 38 0 1
#> 24 23.89 1 38 0 0
#> 24.1 23.89 1 38 0 0
#> 30.1 17.43 1 78 0 0
#> 145.1 10.07 1 65 1 0
#> 114.1 13.68 1 NA 0 0
#> 69 23.23 1 25 0 1
#> 66.2 22.13 1 53 0 0
#> 154 12.63 1 20 1 0
#> 88 18.37 1 47 0 0
#> 181.1 16.46 1 45 0 1
#> 97 19.14 1 65 0 1
#> 10.1 10.53 1 34 0 0
#> 133.1 14.65 1 57 0 0
#> 32.2 20.90 1 37 1 0
#> 128 20.35 1 35 0 1
#> 56.1 12.21 1 60 0 0
#> 189 10.51 1 NA 1 0
#> 175 21.91 1 43 0 0
#> 171 16.57 1 41 0 1
#> 76 19.22 1 54 0 1
#> 113 22.86 1 34 0 0
#> 10.2 10.53 1 34 0 0
#> 14 12.89 1 21 0 0
#> 97.1 19.14 1 65 0 1
#> 189.1 10.51 1 NA 1 0
#> 192 16.44 1 31 1 0
#> 70.1 7.38 1 30 1 0
#> 168 23.72 1 70 0 0
#> 175.1 21.91 1 43 0 0
#> 197.1 21.60 1 69 1 0
#> 179 18.63 1 42 0 0
#> 56.2 12.21 1 60 0 0
#> 169 22.41 1 46 0 0
#> 52 10.42 1 52 0 1
#> 171.1 16.57 1 41 0 1
#> 10.3 10.53 1 34 0 0
#> 32.3 20.90 1 37 1 0
#> 168.1 23.72 1 70 0 0
#> 51.2 18.23 1 83 0 1
#> 168.2 23.72 1 70 0 0
#> 106 16.67 1 49 1 0
#> 177 12.53 1 75 0 0
#> 57 14.46 1 45 0 1
#> 26.3 15.77 1 49 0 1
#> 140 12.68 1 59 1 0
#> 69.1 23.23 1 25 0 1
#> 79 16.23 1 54 1 0
#> 194.2 22.40 1 38 0 1
#> 187 9.92 1 39 1 0
#> 114.2 13.68 1 NA 0 0
#> 114.3 13.68 1 NA 0 0
#> 134 17.81 1 47 1 0
#> 92.1 22.92 1 47 0 1
#> 183 9.24 1 67 1 0
#> 90 20.94 1 50 0 1
#> 15 22.68 1 48 0 0
#> 183.1 9.24 1 67 1 0
#> 170 19.54 1 43 0 1
#> 4 17.64 1 NA 0 1
#> 108 18.29 1 39 0 1
#> 76.1 19.22 1 54 0 1
#> 4.1 17.64 1 NA 0 1
#> 177.1 12.53 1 75 0 0
#> 105 19.75 1 60 0 0
#> 184.1 17.77 1 38 0 0
#> 23 16.92 1 61 0 0
#> 51.3 18.23 1 83 0 1
#> 49.1 12.19 1 48 1 0
#> 66.3 22.13 1 53 0 0
#> 44 24.00 0 56 0 0
#> 11 24.00 0 42 0 1
#> 1 24.00 0 23 1 0
#> 72 24.00 0 40 0 1
#> 11.1 24.00 0 42 0 1
#> 47 24.00 0 38 0 1
#> 82 24.00 0 34 0 0
#> 47.1 24.00 0 38 0 1
#> 80 24.00 0 41 0 0
#> 182 24.00 0 35 0 0
#> 95 24.00 0 68 0 1
#> 46 24.00 0 71 0 0
#> 28 24.00 0 67 1 0
#> 182.1 24.00 0 35 0 0
#> 31 24.00 0 36 0 1
#> 34 24.00 0 36 0 0
#> 146 24.00 0 63 1 0
#> 132 24.00 0 55 0 0
#> 33 24.00 0 53 0 0
#> 28.1 24.00 0 67 1 0
#> 35 24.00 0 51 0 0
#> 152 24.00 0 36 0 1
#> 53 24.00 0 32 0 1
#> 74 24.00 0 43 0 1
#> 109 24.00 0 48 0 0
#> 135 24.00 0 58 1 0
#> 21 24.00 0 47 0 0
#> 146.1 24.00 0 63 1 0
#> 109.1 24.00 0 48 0 0
#> 131 24.00 0 66 0 0
#> 83 24.00 0 6 0 0
#> 147 24.00 0 76 1 0
#> 65 24.00 0 57 1 0
#> 126 24.00 0 48 0 0
#> 2 24.00 0 9 0 0
#> 115 24.00 0 NA 1 0
#> 109.2 24.00 0 48 0 0
#> 82.1 24.00 0 34 0 0
#> 173 24.00 0 19 0 1
#> 17 24.00 0 38 0 1
#> 62 24.00 0 71 0 0
#> 12 24.00 0 63 0 0
#> 12.1 24.00 0 63 0 0
#> 147.1 24.00 0 76 1 0
#> 20 24.00 0 46 1 0
#> 75 24.00 0 21 1 0
#> 161 24.00 0 45 0 0
#> 19 24.00 0 57 0 1
#> 21.1 24.00 0 47 0 0
#> 146.2 24.00 0 63 1 0
#> 22 24.00 0 52 1 0
#> 7 24.00 0 37 1 0
#> 34.1 24.00 0 36 0 0
#> 137 24.00 0 45 1 0
#> 9 24.00 0 31 1 0
#> 172 24.00 0 41 0 0
#> 53.1 24.00 0 32 0 1
#> 126.1 24.00 0 48 0 0
#> 94 24.00 0 51 0 1
#> 3 24.00 0 31 1 0
#> 44.1 24.00 0 56 0 0
#> 147.2 24.00 0 76 1 0
#> 186 24.00 0 45 1 0
#> 151 24.00 0 42 0 0
#> 35.1 24.00 0 51 0 0
#> 2.1 24.00 0 9 0 0
#> 22.1 24.00 0 52 1 0
#> 98 24.00 0 34 1 0
#> 20.1 24.00 0 46 1 0
#> 46.1 24.00 0 71 0 0
#> 151.1 24.00 0 42 0 0
#> 53.2 24.00 0 32 0 1
#> 27 24.00 0 63 1 0
#> 122 24.00 0 66 0 0
#> 22.2 24.00 0 52 1 0
#> 94.1 24.00 0 51 0 1
#> 146.3 24.00 0 63 1 0
#> 165 24.00 0 47 0 0
#> 72.1 24.00 0 40 0 1
#> 11.2 24.00 0 42 0 1
#> 95.1 24.00 0 68 0 1
#> 74.1 24.00 0 43 0 1
#> 46.2 24.00 0 71 0 0
#> 131.1 24.00 0 66 0 0
#> 21.2 24.00 0 47 0 0
#> 12.2 24.00 0 63 0 0
#> 176 24.00 0 43 0 1
#> 196 24.00 0 19 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.610 NA NA NA
#> 2 age, Cure model 0.0115 NA NA NA
#> 3 grade_ii, Cure model 0.0827 NA NA NA
#> 4 grade_iii, Cure model 0.658 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0105 NA NA NA
#> 2 grade_ii, Survival model 0.858 NA NA NA
#> 3 grade_iii, Survival model 0.407 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.60979 0.01147 0.08266 0.65766
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 263.3
#> Residual Deviance: 258 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.60979397 0.01146743 0.08266473 0.65766125
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.01047868 0.85786753 0.40710294
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.91535926 0.62399560 0.82041226 0.71133893 0.37065375 0.75366354
#> [7] 0.97748255 0.84025254 0.57466591 0.41934219 0.89304116 0.74175013
#> [13] 0.99631344 0.79917941 0.92827492 0.75959816 0.82041226 0.71133893
#> [19] 0.31516700 0.64759079 0.95770534 0.94939571 0.89758042 0.99260151
#> [25] 0.77119283 0.82041226 0.85505187 0.98132257 0.60780486 0.98885643
#> [31] 0.90208527 0.54454856 0.86480743 0.85505187 0.64759079 0.45960343
#> [37] 0.92398766 0.57466591 0.53263075 0.94939571 0.45960343 0.41934219
#> [43] 0.09988877 0.09988877 0.75959816 0.95770534 0.27063801 0.45960343
#> [49] 0.87915753 0.69768599 0.79917941 0.67694465 0.92827492 0.84025254
#> [55] 0.57466591 0.61596237 0.90208527 0.50833204 0.78824103 0.66253516
#> [61] 0.35210226 0.92827492 0.86962441 0.67694465 0.80991104 0.98132257
#> [67] 0.19550615 0.50833204 0.54454856 0.69077453 0.90208527 0.40352680
#> [73] 0.94517284 0.78824103 0.92827492 0.57466591 0.19550615 0.71133893
#> [79] 0.19550615 0.78265086 0.88383233 0.85013602 0.82041226 0.87443482
#> [85] 0.27063801 0.81521495 0.41934219 0.96575921 0.73572176 0.31516700
#> [91] 0.96975206 0.56474888 0.38731811 0.96975206 0.63984108 0.70455416
#> [97] 0.66253516 0.88383233 0.63196181 0.74175013 0.77694075 0.71133893
#> [103] 0.91535926 0.45960343 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 49 166 26 51 63 117 16 133 32 194 37 184 91
#> 12.19 19.98 15.77 18.23 22.77 17.46 8.71 14.65 20.90 22.40 12.52 17.77 5.33
#> 181 10 30 26.1 51.1 92 55 145 93 42 25 45 26.2
#> 16.46 10.53 17.43 15.77 18.23 22.92 19.34 10.07 10.33 12.43 6.32 17.42 15.77
#> 81 70 190 77 56 197 123 81.1 58 66 43 32.1 136
#> 14.06 7.38 20.81 7.27 12.21 21.60 13.00 14.06 19.34 22.13 12.10 20.90 21.83
#> 93.1 66.1 194.1 24 24.1 30.1 145.1 69 66.2 154 88 181.1 97
#> 10.33 22.13 22.40 23.89 23.89 17.43 10.07 23.23 22.13 12.63 18.37 16.46 19.14
#> 10.1 133.1 32.2 128 56.1 175 171 76 113 10.2 14 97.1 192
#> 10.53 14.65 20.90 20.35 12.21 21.91 16.57 19.22 22.86 10.53 12.89 19.14 16.44
#> 70.1 168 175.1 197.1 179 56.2 169 52 171.1 10.3 32.3 168.1 51.2
#> 7.38 23.72 21.91 21.60 18.63 12.21 22.41 10.42 16.57 10.53 20.90 23.72 18.23
#> 168.2 106 177 57 26.3 140 69.1 79 194.2 187 134 92.1 183
#> 23.72 16.67 12.53 14.46 15.77 12.68 23.23 16.23 22.40 9.92 17.81 22.92 9.24
#> 90 15 183.1 170 108 76.1 177.1 105 184.1 23 51.3 49.1 66.3
#> 20.94 22.68 9.24 19.54 18.29 19.22 12.53 19.75 17.77 16.92 18.23 12.19 22.13
#> 44 11 1 72 11.1 47 82 47.1 80 182 95 46 28
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 182.1 31 34 146 132 33 28.1 35 152 53 74 109 135
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 21 146.1 109.1 131 83 147 65 126 2 109.2 82.1 173 17
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62 12 12.1 147.1 20 75 161 19 21.1 146.2 22 7 34.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137 9 172 53.1 126.1 94 3 44.1 147.2 186 151 35.1 2.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 22.1 98 20.1 46.1 151.1 53.2 27 122 22.2 94.1 146.3 165 72.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 11.2 95.1 74.1 46.2 131.1 21.2 12.2 176 196
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[94]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.007047919 0.623818558 0.450592414
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.277258864 0.002443547 -0.112422692
#> grade_iii, Cure model
#> 1.460978498
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 129 23.41 1 53 1 0
#> 70 7.38 1 30 1 0
#> 18 15.21 1 49 1 0
#> 108 18.29 1 39 0 1
#> 76 19.22 1 54 0 1
#> 26 15.77 1 49 0 1
#> 166 19.98 1 48 0 0
#> 69 23.23 1 25 0 1
#> 130 16.47 1 53 0 1
#> 187 9.92 1 39 1 0
#> 108.1 18.29 1 39 0 1
#> 145 10.07 1 65 1 0
#> 96 14.54 1 33 0 1
#> 128 20.35 1 35 0 1
#> 78 23.88 1 43 0 0
#> 37 12.52 1 57 1 0
#> 68 20.62 1 44 0 0
#> 24 23.89 1 38 0 0
#> 168 23.72 1 70 0 0
#> 26.1 15.77 1 49 0 1
#> 157 15.10 1 47 0 0
#> 136 21.83 1 43 0 1
#> 49 12.19 1 48 1 0
#> 93 10.33 1 52 0 1
#> 49.1 12.19 1 48 1 0
#> 41 18.02 1 40 1 0
#> 100 16.07 1 60 0 0
#> 117 17.46 1 26 0 1
#> 36 21.19 1 48 0 1
#> 55 19.34 1 69 0 1
#> 32 20.90 1 37 1 0
#> 14 12.89 1 21 0 0
#> 107 11.18 1 54 1 0
#> 180 14.82 1 37 0 0
#> 16 8.71 1 71 0 1
#> 10 10.53 1 34 0 0
#> 32.1 20.90 1 37 1 0
#> 81 14.06 1 34 0 0
#> 134 17.81 1 47 1 0
#> 128.1 20.35 1 35 0 1
#> 89 11.44 1 NA 0 0
#> 36.1 21.19 1 48 0 1
#> 66 22.13 1 53 0 0
#> 79 16.23 1 54 1 0
#> 130.1 16.47 1 53 0 1
#> 42 12.43 1 49 0 1
#> 170 19.54 1 43 0 1
#> 50 10.02 1 NA 1 0
#> 155 13.08 1 26 0 0
#> 16.1 8.71 1 71 0 1
#> 63 22.77 1 31 1 0
#> 167 15.55 1 56 1 0
#> 139 21.49 1 63 1 0
#> 49.2 12.19 1 48 1 0
#> 136.1 21.83 1 43 0 1
#> 189 10.51 1 NA 1 0
#> 101 9.97 1 10 0 1
#> 36.2 21.19 1 48 0 1
#> 184 17.77 1 38 0 0
#> 149 8.37 1 33 1 0
#> 42.1 12.43 1 49 0 1
#> 159 10.55 1 50 0 1
#> 90 20.94 1 50 0 1
#> 125 15.65 1 67 1 0
#> 15 22.68 1 48 0 0
#> 188 16.16 1 46 0 1
#> 140 12.68 1 59 1 0
#> 125.1 15.65 1 67 1 0
#> 136.2 21.83 1 43 0 1
#> 29 15.45 1 68 1 0
#> 50.1 10.02 1 NA 1 0
#> 78.1 23.88 1 43 0 0
#> 128.2 20.35 1 35 0 1
#> 128.3 20.35 1 35 0 1
#> 89.1 11.44 1 NA 0 0
#> 194 22.40 1 38 0 1
#> 133 14.65 1 57 0 0
#> 52 10.42 1 52 0 1
#> 97 19.14 1 65 0 1
#> 56 12.21 1 60 0 0
#> 129.1 23.41 1 53 1 0
#> 29.1 15.45 1 68 1 0
#> 127 3.53 1 62 0 1
#> 134.1 17.81 1 47 1 0
#> 93.1 10.33 1 52 0 1
#> 157.1 15.10 1 47 0 0
#> 55.1 19.34 1 69 0 1
#> 114 13.68 1 NA 0 0
#> 25 6.32 1 34 1 0
#> 113 22.86 1 34 0 0
#> 107.1 11.18 1 54 1 0
#> 127.1 3.53 1 62 0 1
#> 188.1 16.16 1 46 0 1
#> 10.1 10.53 1 34 0 0
#> 66.1 22.13 1 53 0 0
#> 100.1 16.07 1 60 0 0
#> 4 17.64 1 NA 0 1
#> 166.1 19.98 1 48 0 0
#> 8 18.43 1 32 0 0
#> 4.1 17.64 1 NA 0 1
#> 13 14.34 1 54 0 1
#> 45 17.42 1 54 0 1
#> 88 18.37 1 47 0 0
#> 51 18.23 1 83 0 1
#> 60 13.15 1 38 1 0
#> 197 21.60 1 69 1 0
#> 194.1 22.40 1 38 0 1
#> 117.1 17.46 1 26 0 1
#> 8.1 18.43 1 32 0 0
#> 37.1 12.52 1 57 1 0
#> 8.2 18.43 1 32 0 0
#> 107.2 11.18 1 54 1 0
#> 44 24.00 0 56 0 0
#> 185 24.00 0 44 1 0
#> 80 24.00 0 41 0 0
#> 48 24.00 0 31 1 0
#> 119 24.00 0 17 0 0
#> 144 24.00 0 28 0 1
#> 142 24.00 0 53 0 0
#> 75 24.00 0 21 1 0
#> 135 24.00 0 58 1 0
#> 104 24.00 0 50 1 0
#> 191 24.00 0 60 0 1
#> 172 24.00 0 41 0 0
#> 121 24.00 0 57 1 0
#> 163 24.00 0 66 0 0
#> 27 24.00 0 63 1 0
#> 11 24.00 0 42 0 1
#> 137 24.00 0 45 1 0
#> 98 24.00 0 34 1 0
#> 185.1 24.00 0 44 1 0
#> 146 24.00 0 63 1 0
#> 35 24.00 0 51 0 0
#> 186 24.00 0 45 1 0
#> 121.1 24.00 0 57 1 0
#> 151 24.00 0 42 0 0
#> 44.1 24.00 0 56 0 0
#> 132 24.00 0 55 0 0
#> 84 24.00 0 39 0 1
#> 104.1 24.00 0 50 1 0
#> 156 24.00 0 50 1 0
#> 98.1 24.00 0 34 1 0
#> 104.2 24.00 0 50 1 0
#> 191.1 24.00 0 60 0 1
#> 185.2 24.00 0 44 1 0
#> 156.1 24.00 0 50 1 0
#> 104.3 24.00 0 50 1 0
#> 143 24.00 0 51 0 0
#> 122 24.00 0 66 0 0
#> 82 24.00 0 34 0 0
#> 120 24.00 0 68 0 1
#> 160 24.00 0 31 1 0
#> 73 24.00 0 NA 0 1
#> 165 24.00 0 47 0 0
#> 172.1 24.00 0 41 0 0
#> 98.2 24.00 0 34 1 0
#> 71 24.00 0 51 0 0
#> 44.2 24.00 0 56 0 0
#> 82.1 24.00 0 34 0 0
#> 160.1 24.00 0 31 1 0
#> 21 24.00 0 47 0 0
#> 172.2 24.00 0 41 0 0
#> 182 24.00 0 35 0 0
#> 22 24.00 0 52 1 0
#> 191.2 24.00 0 60 0 1
#> 160.2 24.00 0 31 1 0
#> 9 24.00 0 31 1 0
#> 148 24.00 0 61 1 0
#> 146.1 24.00 0 63 1 0
#> 161 24.00 0 45 0 0
#> 193 24.00 0 45 0 1
#> 174 24.00 0 49 1 0
#> 200 24.00 0 64 0 0
#> 9.1 24.00 0 31 1 0
#> 162 24.00 0 51 0 0
#> 103 24.00 0 56 1 0
#> 48.1 24.00 0 31 1 0
#> 161.1 24.00 0 45 0 0
#> 200.1 24.00 0 64 0 0
#> 118 24.00 0 44 1 0
#> 98.3 24.00 0 34 1 0
#> 173 24.00 0 19 0 1
#> 28 24.00 0 67 1 0
#> 191.3 24.00 0 60 0 1
#> 75.1 24.00 0 21 1 0
#> 165.1 24.00 0 47 0 0
#> 193.1 24.00 0 45 0 1
#> 146.2 24.00 0 63 1 0
#> 161.2 24.00 0 45 0 0
#> 46 24.00 0 71 0 0
#> 28.1 24.00 0 67 1 0
#> 174.1 24.00 0 49 1 0
#> 126 24.00 0 48 0 0
#> 44.3 24.00 0 56 0 0
#> 138 24.00 0 44 1 0
#> 152 24.00 0 36 0 1
#> 80.1 24.00 0 41 0 0
#> 80.2 24.00 0 41 0 0
#> 22.1 24.00 0 52 1 0
#> 135.1 24.00 0 58 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.277 NA NA NA
#> 2 age, Cure model 0.00244 NA NA NA
#> 3 grade_ii, Cure model -0.112 NA NA NA
#> 4 grade_iii, Cure model 1.46 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00705 NA NA NA
#> 2 grade_ii, Survival model 0.624 NA NA NA
#> 3 grade_iii, Survival model 0.451 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.277259 0.002444 -0.112423 1.460978
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 263.3
#> Residual Deviance: 243.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.277258864 0.002443547 -0.112422692 1.460978498
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.007047919 0.623818558 0.450592414
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.20544351 0.98180364 0.79980112 0.63893660 0.59126877 0.75734950
#> [7] 0.54832113 0.24610442 0.71146914 0.96312571 0.63893660 0.95356704
#> [13] 0.82849494 0.51315301 0.10460089 0.86758738 0.50343644 0.04867217
#> [19] 0.17213361 0.75734950 0.80558289 0.38009361 0.89410268 0.94392190
#> [25] 0.89410268 0.66179249 0.74451140 0.69059760 0.44236166 0.57470251
#> [31] 0.48405618 0.85654649 0.90938854 0.81704057 0.96786272 0.92918765
#> [37] 0.48405618 0.83980312 0.66920926 0.51315301 0.44236166 0.35081422
#> [43] 0.72491063 0.71146914 0.87828757 0.56596508 0.85098799 0.96786272
#> [49] 0.28524014 0.78211043 0.43064972 0.89410268 0.38009361 0.95835452
#> [55] 0.44236166 0.68345845 0.97716922 0.87828757 0.92424241 0.47366978
#> [61] 0.76992822 0.30301848 0.73155573 0.86209925 0.76992822 0.38009361
#> [67] 0.78814202 0.10460089 0.51315301 0.51315301 0.32038701 0.82277761
#> [73] 0.93902352 0.59946095 0.88883149 0.20544351 0.78814202 0.99098640
#> [79] 0.66920926 0.94392190 0.80558289 0.57470251 0.98640967 0.26586683
#> [85] 0.90938854 0.99098640 0.73155573 0.92918765 0.35081422 0.74451140
#> [91] 0.54832113 0.60749061 0.83417386 0.70454821 0.63102970 0.65425116
#> [97] 0.84542217 0.41829648 0.32038701 0.69059760 0.60749061 0.86758738
#> [103] 0.60749061 0.90938854 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 129 70 18 108 76 26 166 69 130 187 108.1 145 96
#> 23.41 7.38 15.21 18.29 19.22 15.77 19.98 23.23 16.47 9.92 18.29 10.07 14.54
#> 128 78 37 68 24 168 26.1 157 136 49 93 49.1 41
#> 20.35 23.88 12.52 20.62 23.89 23.72 15.77 15.10 21.83 12.19 10.33 12.19 18.02
#> 100 117 36 55 32 14 107 180 16 10 32.1 81 134
#> 16.07 17.46 21.19 19.34 20.90 12.89 11.18 14.82 8.71 10.53 20.90 14.06 17.81
#> 128.1 36.1 66 79 130.1 42 170 155 16.1 63 167 139 49.2
#> 20.35 21.19 22.13 16.23 16.47 12.43 19.54 13.08 8.71 22.77 15.55 21.49 12.19
#> 136.1 101 36.2 184 149 42.1 159 90 125 15 188 140 125.1
#> 21.83 9.97 21.19 17.77 8.37 12.43 10.55 20.94 15.65 22.68 16.16 12.68 15.65
#> 136.2 29 78.1 128.2 128.3 194 133 52 97 56 129.1 29.1 127
#> 21.83 15.45 23.88 20.35 20.35 22.40 14.65 10.42 19.14 12.21 23.41 15.45 3.53
#> 134.1 93.1 157.1 55.1 25 113 107.1 127.1 188.1 10.1 66.1 100.1 166.1
#> 17.81 10.33 15.10 19.34 6.32 22.86 11.18 3.53 16.16 10.53 22.13 16.07 19.98
#> 8 13 45 88 51 60 197 194.1 117.1 8.1 37.1 8.2 107.2
#> 18.43 14.34 17.42 18.37 18.23 13.15 21.60 22.40 17.46 18.43 12.52 18.43 11.18
#> 44 185 80 48 119 144 142 75 135 104 191 172 121
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 163 27 11 137 98 185.1 146 35 186 121.1 151 44.1 132
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 84 104.1 156 98.1 104.2 191.1 185.2 156.1 104.3 143 122 82 120
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 160 165 172.1 98.2 71 44.2 82.1 160.1 21 172.2 182 22 191.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 160.2 9 148 146.1 161 193 174 200 9.1 162 103 48.1 161.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 200.1 118 98.3 173 28 191.3 75.1 165.1 193.1 146.2 161.2 46 28.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174.1 126 44.3 138 152 80.1 80.2 22.1 135.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[95]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.01842703 0.26342709 -0.20616827
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.1943191259 -0.0008465609 0.0292927385
#> grade_iii, Cure model
#> 1.1321555376
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 177 12.53 1 75 0 0
#> 99 21.19 1 38 0 1
#> 181 16.46 1 45 0 1
#> 114 13.68 1 NA 0 0
#> 52 10.42 1 52 0 1
#> 199 19.81 1 NA 0 1
#> 128 20.35 1 35 0 1
#> 130 16.47 1 53 0 1
#> 92 22.92 1 47 0 1
#> 97 19.14 1 65 0 1
#> 183 9.24 1 67 1 0
#> 134 17.81 1 47 1 0
#> 145 10.07 1 65 1 0
#> 68 20.62 1 44 0 0
#> 90 20.94 1 50 0 1
#> 6 15.64 1 39 0 0
#> 183.1 9.24 1 67 1 0
#> 108 18.29 1 39 0 1
#> 187 9.92 1 39 1 0
#> 199.1 19.81 1 NA 0 1
#> 195 11.76 1 NA 1 0
#> 184 17.77 1 38 0 0
#> 181.1 16.46 1 45 0 1
#> 145.1 10.07 1 65 1 0
#> 61 10.12 1 36 0 1
#> 40 18.00 1 28 1 0
#> 150 20.33 1 48 0 0
#> 79 16.23 1 54 1 0
#> 42 12.43 1 49 0 1
#> 77 7.27 1 67 0 1
#> 123 13.00 1 44 1 0
#> 88 18.37 1 47 0 0
#> 4 17.64 1 NA 0 1
#> 124 9.73 1 NA 1 0
#> 157 15.10 1 47 0 0
#> 45 17.42 1 54 0 1
#> 92.1 22.92 1 47 0 1
#> 29 15.45 1 68 1 0
#> 114.1 13.68 1 NA 0 0
#> 136 21.83 1 43 0 1
#> 57 14.46 1 45 0 1
#> 110 17.56 1 65 0 1
#> 29.1 15.45 1 68 1 0
#> 166 19.98 1 48 0 0
#> 99.1 21.19 1 38 0 1
#> 130.1 16.47 1 53 0 1
#> 108.1 18.29 1 39 0 1
#> 159 10.55 1 50 0 1
#> 97.1 19.14 1 65 0 1
#> 23 16.92 1 61 0 0
#> 140 12.68 1 59 1 0
#> 36 21.19 1 48 0 1
#> 66 22.13 1 53 0 0
#> 14 12.89 1 21 0 0
#> 16 8.71 1 71 0 1
#> 61.1 10.12 1 36 0 1
#> 77.1 7.27 1 67 0 1
#> 36.1 21.19 1 48 0 1
#> 52.1 10.42 1 52 0 1
#> 133 14.65 1 57 0 0
#> 76 19.22 1 54 0 1
#> 55 19.34 1 69 0 1
#> 154 12.63 1 20 1 0
#> 58 19.34 1 39 0 0
#> 69 23.23 1 25 0 1
#> 63 22.77 1 31 1 0
#> 133.1 14.65 1 57 0 0
#> 32 20.90 1 37 1 0
#> 170 19.54 1 43 0 1
#> 70 7.38 1 30 1 0
#> 188 16.16 1 46 0 1
#> 158 20.14 1 74 1 0
#> 50 10.02 1 NA 1 0
#> 59 10.16 1 NA 1 0
#> 117 17.46 1 26 0 1
#> 15 22.68 1 48 0 0
#> 153 21.33 1 55 1 0
#> 113 22.86 1 34 0 0
#> 184.1 17.77 1 38 0 0
#> 92.2 22.92 1 47 0 1
#> 86 23.81 1 58 0 1
#> 16.1 8.71 1 71 0 1
#> 111 17.45 1 47 0 1
#> 89 11.44 1 NA 0 0
#> 92.3 22.92 1 47 0 1
#> 79.1 16.23 1 54 1 0
#> 59.1 10.16 1 NA 1 0
#> 50.1 10.02 1 NA 1 0
#> 175 21.91 1 43 0 0
#> 41 18.02 1 40 1 0
#> 166.1 19.98 1 48 0 0
#> 97.2 19.14 1 65 0 1
#> 136.1 21.83 1 43 0 1
#> 114.2 13.68 1 NA 0 0
#> 114.3 13.68 1 NA 0 0
#> 63.1 22.77 1 31 1 0
#> 10 10.53 1 34 0 0
#> 106 16.67 1 49 1 0
#> 76.1 19.22 1 54 0 1
#> 90.1 20.94 1 50 0 1
#> 192 16.44 1 31 1 0
#> 93 10.33 1 52 0 1
#> 184.2 17.77 1 38 0 0
#> 157.1 15.10 1 47 0 0
#> 181.2 16.46 1 45 0 1
#> 106.1 16.67 1 49 1 0
#> 139 21.49 1 63 1 0
#> 42.1 12.43 1 49 0 1
#> 39 15.59 1 37 0 1
#> 5 16.43 1 51 0 1
#> 184.3 17.77 1 38 0 0
#> 60 13.15 1 38 1 0
#> 196 24.00 0 19 0 0
#> 27 24.00 0 63 1 0
#> 122 24.00 0 66 0 0
#> 148 24.00 0 61 1 0
#> 53 24.00 0 32 0 1
#> 148.1 24.00 0 61 1 0
#> 152 24.00 0 36 0 1
#> 9 24.00 0 31 1 0
#> 156 24.00 0 50 1 0
#> 120 24.00 0 68 0 1
#> 27.1 24.00 0 63 1 0
#> 152.1 24.00 0 36 0 1
#> 73 24.00 0 NA 0 1
#> 75 24.00 0 21 1 0
#> 83 24.00 0 6 0 0
#> 62 24.00 0 71 0 0
#> 83.1 24.00 0 6 0 0
#> 64 24.00 0 43 0 0
#> 115 24.00 0 NA 1 0
#> 20 24.00 0 46 1 0
#> 17 24.00 0 38 0 1
#> 102 24.00 0 49 0 0
#> 80 24.00 0 41 0 0
#> 141 24.00 0 44 1 0
#> 174 24.00 0 49 1 0
#> 7 24.00 0 37 1 0
#> 65 24.00 0 57 1 0
#> 115.1 24.00 0 NA 1 0
#> 126 24.00 0 48 0 0
#> 198 24.00 0 66 0 1
#> 53.1 24.00 0 32 0 1
#> 148.2 24.00 0 61 1 0
#> 102.1 24.00 0 49 0 0
#> 193 24.00 0 45 0 1
#> 146 24.00 0 63 1 0
#> 54 24.00 0 53 1 0
#> 148.3 24.00 0 61 1 0
#> 119 24.00 0 17 0 0
#> 193.1 24.00 0 45 0 1
#> 95 24.00 0 68 0 1
#> 112 24.00 0 61 0 0
#> 185 24.00 0 44 1 0
#> 65.1 24.00 0 57 1 0
#> 73.1 24.00 0 NA 0 1
#> 191 24.00 0 60 0 1
#> 71 24.00 0 51 0 0
#> 34 24.00 0 36 0 0
#> 95.1 24.00 0 68 0 1
#> 28 24.00 0 67 1 0
#> 115.2 24.00 0 NA 1 0
#> 148.4 24.00 0 61 1 0
#> 148.5 24.00 0 61 1 0
#> 148.6 24.00 0 61 1 0
#> 152.2 24.00 0 36 0 1
#> 71.1 24.00 0 51 0 0
#> 11 24.00 0 42 0 1
#> 178 24.00 0 52 1 0
#> 109 24.00 0 48 0 0
#> 138 24.00 0 44 1 0
#> 95.2 24.00 0 68 0 1
#> 163 24.00 0 66 0 0
#> 115.3 24.00 0 NA 1 0
#> 19 24.00 0 57 0 1
#> 143 24.00 0 51 0 0
#> 48 24.00 0 31 1 0
#> 27.2 24.00 0 63 1 0
#> 172 24.00 0 41 0 0
#> 144 24.00 0 28 0 1
#> 94 24.00 0 51 0 1
#> 83.2 24.00 0 6 0 0
#> 102.2 24.00 0 49 0 0
#> 126.1 24.00 0 48 0 0
#> 21 24.00 0 47 0 0
#> 73.2 24.00 0 NA 0 1
#> 138.1 24.00 0 44 1 0
#> 120.1 24.00 0 68 0 1
#> 83.3 24.00 0 6 0 0
#> 27.3 24.00 0 63 1 0
#> 118 24.00 0 44 1 0
#> 156.1 24.00 0 50 1 0
#> 143.1 24.00 0 51 0 0
#> 162 24.00 0 51 0 0
#> 31 24.00 0 36 0 1
#> 27.4 24.00 0 63 1 0
#> 143.2 24.00 0 51 0 0
#> 131 24.00 0 66 0 0
#> 75.1 24.00 0 21 1 0
#> 122.1 24.00 0 66 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.194 NA NA NA
#> 2 age, Cure model -0.000847 NA NA NA
#> 3 grade_ii, Cure model 0.0293 NA NA NA
#> 4 grade_iii, Cure model 1.13 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0184 NA NA NA
#> 2 grade_ii, Survival model 0.263 NA NA NA
#> 3 grade_iii, Survival model -0.206 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.1943191 -0.0008466 0.0292927 1.1321555
#>
#> Degrees of Freedom: 178 Total (i.e. Null); 175 Residual
#> Null Deviance: 246.5
#> Residual Deviance: 234.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.1943191259 -0.0008465609 0.0292927385 1.1321555376
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.01842703 0.26342709 -0.20616827
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.9105422 0.4642006 0.7918069 0.9342348 0.5514228 0.7796725 0.2089756
#> [8] 0.6407035 0.9706175 0.7004600 0.9573056 0.5410441 0.5086780 0.8382848
#> [15] 0.9706175 0.6710793 0.9661961 0.7075366 0.7918069 0.9573056 0.9481331
#> [22] 0.6932306 0.5616950 0.8213677 0.9153401 0.9917644 0.8908067 0.6635094
#> [29] 0.8600461 0.7543322 0.2089756 0.8494413 0.4087014 0.8806745 0.7343494
#> [36] 0.8494413 0.5810498 0.4642006 0.7796725 0.6710793 0.9248110 0.6407035
#> [43] 0.7608811 0.9007700 0.4642006 0.3760334 0.8957949 0.9791703 0.9481331
#> [50] 0.9917644 0.4642006 0.9342348 0.8704739 0.6244194 0.6076087 0.9056677
#> [57] 0.6076087 0.1590039 0.3200687 0.8704739 0.5304105 0.5987813 0.9875754
#> [64] 0.8326559 0.5717069 0.7410413 0.3579571 0.4516545 0.2968331 0.7075366
#> [71] 0.2089756 0.1042576 0.9791703 0.7477144 0.2089756 0.8213677 0.3927775
#> [78] 0.6859110 0.5810498 0.6407035 0.4087014 0.3200687 0.9295333 0.7673149
#> [85] 0.6244194 0.5086780 0.8095866 0.9435098 0.7075366 0.8600461 0.7918069
#> [92] 0.7673149 0.4381378 0.9153401 0.8438743 0.8155002 0.7075366 0.8857641
#> [99] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [106] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000 0.0000000
#>
#> $Time
#> 177 99 181 52 128 130 92 97 183 134 145 68 90
#> 12.53 21.19 16.46 10.42 20.35 16.47 22.92 19.14 9.24 17.81 10.07 20.62 20.94
#> 6 183.1 108 187 184 181.1 145.1 61 40 150 79 42 77
#> 15.64 9.24 18.29 9.92 17.77 16.46 10.07 10.12 18.00 20.33 16.23 12.43 7.27
#> 123 88 157 45 92.1 29 136 57 110 29.1 166 99.1 130.1
#> 13.00 18.37 15.10 17.42 22.92 15.45 21.83 14.46 17.56 15.45 19.98 21.19 16.47
#> 108.1 159 97.1 23 140 36 66 14 16 61.1 77.1 36.1 52.1
#> 18.29 10.55 19.14 16.92 12.68 21.19 22.13 12.89 8.71 10.12 7.27 21.19 10.42
#> 133 76 55 154 58 69 63 133.1 32 170 70 188 158
#> 14.65 19.22 19.34 12.63 19.34 23.23 22.77 14.65 20.90 19.54 7.38 16.16 20.14
#> 117 15 153 113 184.1 92.2 86 16.1 111 92.3 79.1 175 41
#> 17.46 22.68 21.33 22.86 17.77 22.92 23.81 8.71 17.45 22.92 16.23 21.91 18.02
#> 166.1 97.2 136.1 63.1 10 106 76.1 90.1 192 93 184.2 157.1 181.2
#> 19.98 19.14 21.83 22.77 10.53 16.67 19.22 20.94 16.44 10.33 17.77 15.10 16.46
#> 106.1 139 42.1 39 5 184.3 60 196 27 122 148 53 148.1
#> 16.67 21.49 12.43 15.59 16.43 17.77 13.15 24.00 24.00 24.00 24.00 24.00 24.00
#> 152 9 156 120 27.1 152.1 75 83 62 83.1 64 20 17
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 102 80 141 174 7 65 126 198 53.1 148.2 102.1 193 146
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 54 148.3 119 193.1 95 112 185 65.1 191 71 34 95.1 28
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148.4 148.5 148.6 152.2 71.1 11 178 109 138 95.2 163 19 143
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 48 27.2 172 144 94 83.2 102.2 126.1 21 138.1 120.1 83.3 27.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 118 156.1 143.1 162 31 27.4 143.2 131 75.1 122.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[96]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.0007171975 0.5037089710 -0.1234541085
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.13476562 0.01893705 0.38306276
#> grade_iii, Cure model
#> 1.04180912
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 5 16.43 1 51 0 1
#> 32 20.90 1 37 1 0
#> 59 10.16 1 NA 1 0
#> 66 22.13 1 53 0 0
#> 97 19.14 1 65 0 1
#> 189 10.51 1 NA 1 0
#> 100 16.07 1 60 0 0
#> 110 17.56 1 65 0 1
#> 23 16.92 1 61 0 0
#> 150 20.33 1 48 0 0
#> 170 19.54 1 43 0 1
#> 59.1 10.16 1 NA 1 0
#> 88 18.37 1 47 0 0
#> 96 14.54 1 33 0 1
#> 136 21.83 1 43 0 1
#> 110.1 17.56 1 65 0 1
#> 189.1 10.51 1 NA 1 0
#> 107 11.18 1 54 1 0
#> 58 19.34 1 39 0 0
#> 25 6.32 1 34 1 0
#> 108 18.29 1 39 0 1
#> 140 12.68 1 59 1 0
#> 6 15.64 1 39 0 0
#> 58.1 19.34 1 39 0 0
#> 107.1 11.18 1 54 1 0
#> 61 10.12 1 36 0 1
#> 4 17.64 1 NA 0 1
#> 164 23.60 1 76 0 1
#> 36 21.19 1 48 0 1
#> 10 10.53 1 34 0 0
#> 99 21.19 1 38 0 1
#> 106 16.67 1 49 1 0
#> 41 18.02 1 40 1 0
#> 52 10.42 1 52 0 1
#> 79 16.23 1 54 1 0
#> 56 12.21 1 60 0 0
#> 179 18.63 1 42 0 0
#> 181 16.46 1 45 0 1
#> 183 9.24 1 67 1 0
#> 32.1 20.90 1 37 1 0
#> 76 19.22 1 54 0 1
#> 175 21.91 1 43 0 0
#> 164.1 23.60 1 76 0 1
#> 190 20.81 1 42 1 0
#> 97.1 19.14 1 65 0 1
#> 52.1 10.42 1 52 0 1
#> 183.1 9.24 1 67 1 0
#> 37 12.52 1 57 1 0
#> 55 19.34 1 69 0 1
#> 61.1 10.12 1 36 0 1
#> 117 17.46 1 26 0 1
#> 60 13.15 1 38 1 0
#> 61.2 10.12 1 36 0 1
#> 15 22.68 1 48 0 0
#> 40 18.00 1 28 1 0
#> 16 8.71 1 71 0 1
#> 79.1 16.23 1 54 1 0
#> 155 13.08 1 26 0 0
#> 39 15.59 1 37 0 1
#> 99.1 21.19 1 38 0 1
#> 41.1 18.02 1 40 1 0
#> 124 9.73 1 NA 1 0
#> 99.2 21.19 1 38 0 1
#> 111 17.45 1 47 0 1
#> 177 12.53 1 75 0 0
#> 117.1 17.46 1 26 0 1
#> 171 16.57 1 41 0 1
#> 85 16.44 1 36 0 0
#> 50 10.02 1 NA 1 0
#> 177.1 12.53 1 75 0 0
#> 61.3 10.12 1 36 0 1
#> 77 7.27 1 67 0 1
#> 149 8.37 1 33 1 0
#> 6.1 15.64 1 39 0 0
#> 125 15.65 1 67 1 0
#> 36.1 21.19 1 48 0 1
#> 6.2 15.64 1 39 0 0
#> 197 21.60 1 69 1 0
#> 108.1 18.29 1 39 0 1
#> 154 12.63 1 20 1 0
#> 107.2 11.18 1 54 1 0
#> 86 23.81 1 58 0 1
#> 68 20.62 1 44 0 0
#> 79.2 16.23 1 54 1 0
#> 114 13.68 1 NA 0 0
#> 5.1 16.43 1 51 0 1
#> 81 14.06 1 34 0 0
#> 180 14.82 1 37 0 0
#> 155.1 13.08 1 26 0 0
#> 158 20.14 1 74 1 0
#> 41.2 18.02 1 40 1 0
#> 76.1 19.22 1 54 0 1
#> 8 18.43 1 32 0 0
#> 41.3 18.02 1 40 1 0
#> 14 12.89 1 21 0 0
#> 43 12.10 1 61 0 1
#> 189.2 10.51 1 NA 1 0
#> 175.1 21.91 1 43 0 0
#> 92 22.92 1 47 0 1
#> 187 9.92 1 39 1 0
#> 24 23.89 1 38 0 0
#> 107.3 11.18 1 54 1 0
#> 123 13.00 1 44 1 0
#> 190.1 20.81 1 42 1 0
#> 60.1 13.15 1 38 1 0
#> 69 23.23 1 25 0 1
#> 92.1 22.92 1 47 0 1
#> 145 10.07 1 65 1 0
#> 25.1 6.32 1 34 1 0
#> 16.1 8.71 1 71 0 1
#> 63 22.77 1 31 1 0
#> 183.2 9.24 1 67 1 0
#> 173 24.00 0 19 0 1
#> 142 24.00 0 53 0 0
#> 67 24.00 0 25 0 0
#> 161 24.00 0 45 0 0
#> 148 24.00 0 61 1 0
#> 22 24.00 0 52 1 0
#> 35 24.00 0 51 0 0
#> 62 24.00 0 71 0 0
#> 193 24.00 0 45 0 1
#> 53 24.00 0 32 0 1
#> 131 24.00 0 66 0 0
#> 173.1 24.00 0 19 0 1
#> 118 24.00 0 44 1 0
#> 131.1 24.00 0 66 0 0
#> 2 24.00 0 9 0 0
#> 82 24.00 0 34 0 0
#> 116 24.00 0 58 0 1
#> 1 24.00 0 23 1 0
#> 118.1 24.00 0 44 1 0
#> 186 24.00 0 45 1 0
#> 119 24.00 0 17 0 0
#> 65 24.00 0 57 1 0
#> 102 24.00 0 49 0 0
#> 148.1 24.00 0 61 1 0
#> 173.2 24.00 0 19 0 1
#> 83 24.00 0 6 0 0
#> 47 24.00 0 38 0 1
#> 82.1 24.00 0 34 0 0
#> 161.1 24.00 0 45 0 0
#> 112 24.00 0 61 0 0
#> 143 24.00 0 51 0 0
#> 3 24.00 0 31 1 0
#> 7 24.00 0 37 1 0
#> 82.2 24.00 0 34 0 0
#> 72 24.00 0 40 0 1
#> 116.1 24.00 0 58 0 1
#> 126 24.00 0 48 0 0
#> 172 24.00 0 41 0 0
#> 53.1 24.00 0 32 0 1
#> 148.2 24.00 0 61 1 0
#> 48 24.00 0 31 1 0
#> 44 24.00 0 56 0 0
#> 161.2 24.00 0 45 0 0
#> 17 24.00 0 38 0 1
#> 151 24.00 0 42 0 0
#> 22.1 24.00 0 52 1 0
#> 11 24.00 0 42 0 1
#> 87 24.00 0 27 0 0
#> 2.1 24.00 0 9 0 0
#> 12 24.00 0 63 0 0
#> 80 24.00 0 41 0 0
#> 144 24.00 0 28 0 1
#> 1.1 24.00 0 23 1 0
#> 94 24.00 0 51 0 1
#> 64 24.00 0 43 0 0
#> 191 24.00 0 60 0 1
#> 33 24.00 0 53 0 0
#> 21 24.00 0 47 0 0
#> 119.1 24.00 0 17 0 0
#> 147 24.00 0 76 1 0
#> 178 24.00 0 52 1 0
#> 135 24.00 0 58 1 0
#> 87.1 24.00 0 27 0 0
#> 196 24.00 0 19 0 0
#> 174 24.00 0 49 1 0
#> 87.2 24.00 0 27 0 0
#> 22.2 24.00 0 52 1 0
#> 22.3 24.00 0 52 1 0
#> 94.1 24.00 0 51 0 1
#> 112.1 24.00 0 61 0 0
#> 196.1 24.00 0 19 0 0
#> 193.1 24.00 0 45 0 1
#> 73 24.00 0 NA 0 1
#> 82.3 24.00 0 34 0 0
#> 165 24.00 0 47 0 0
#> 27 24.00 0 63 1 0
#> 146 24.00 0 63 1 0
#> 104 24.00 0 50 1 0
#> 141 24.00 0 44 1 0
#> 186.1 24.00 0 45 1 0
#> 173.3 24.00 0 19 0 1
#> 34 24.00 0 36 0 0
#> 156 24.00 0 50 1 0
#> 3.1 24.00 0 31 1 0
#> 186.2 24.00 0 45 1 0
#> 186.3 24.00 0 45 1 0
#> 120 24.00 0 68 0 1
#> 118.2 24.00 0 44 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.13 NA NA NA
#> 2 age, Cure model 0.0189 NA NA NA
#> 3 grade_ii, Cure model 0.383 NA NA NA
#> 4 grade_iii, Cure model 1.04 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.000717 NA NA NA
#> 2 grade_ii, Survival model 0.504 NA NA NA
#> 3 grade_iii, Survival model -0.123 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.13477 0.01894 0.38306 1.04181
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 262
#> Residual Deviance: 249.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.13476562 0.01893705 0.38306276 1.04180912
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.0007171975 0.5037089710 -0.1234541085
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.581757735 0.237639922 0.123330629 0.370227457 0.627399615 0.487631976
#> [7] 0.534678748 0.290055012 0.310544995 0.410719733 0.690146883 0.159734623
#> [13] 0.487631976 0.821030913 0.320689143 0.984170774 0.420892181 0.760896524
#> [19] 0.645514873 0.320689143 0.821030913 0.878601786 0.034596894 0.184077739
#> [25] 0.853756437 0.184077739 0.544174794 0.441079179 0.862056128 0.600461942
#> [31] 0.803925987 0.390351575 0.562947456 0.928007024 0.237639922 0.350184162
#> [37] 0.135892486 0.034596894 0.259252926 0.370227457 0.862056128 0.928007024
#> [43] 0.795372974 0.320689143 0.878601786 0.506368911 0.708171190 0.878601786
#> [49] 0.110720171 0.478198857 0.952011556 0.600461942 0.725766329 0.672138847
#> [55] 0.184077739 0.441079179 0.184077739 0.525175159 0.778226169 0.506368911
#> [61] 0.553553980 0.572354615 0.778226169 0.878601786 0.976133787 0.968101604
#> [67] 0.645514873 0.636504693 0.184077739 0.645514873 0.172223412 0.420892181
#> [73] 0.769594454 0.821030913 0.020711494 0.279666951 0.600461942 0.581757735
#> [79] 0.699160470 0.681144465 0.725766329 0.300430100 0.441079179 0.350184162
#> [85] 0.400538652 0.441079179 0.752125769 0.812475001 0.135892486 0.072237765
#> [91] 0.919777415 0.007826961 0.821030913 0.743353464 0.259252926 0.708171190
#> [97] 0.058434271 0.072237765 0.911495804 0.984170774 0.952011556 0.098060841
#> [103] 0.928007024 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 5 32 66 97 100 110 23 150 170 88 96 136 110.1
#> 16.43 20.90 22.13 19.14 16.07 17.56 16.92 20.33 19.54 18.37 14.54 21.83 17.56
#> 107 58 25 108 140 6 58.1 107.1 61 164 36 10 99
#> 11.18 19.34 6.32 18.29 12.68 15.64 19.34 11.18 10.12 23.60 21.19 10.53 21.19
#> 106 41 52 79 56 179 181 183 32.1 76 175 164.1 190
#> 16.67 18.02 10.42 16.23 12.21 18.63 16.46 9.24 20.90 19.22 21.91 23.60 20.81
#> 97.1 52.1 183.1 37 55 61.1 117 60 61.2 15 40 16 79.1
#> 19.14 10.42 9.24 12.52 19.34 10.12 17.46 13.15 10.12 22.68 18.00 8.71 16.23
#> 155 39 99.1 41.1 99.2 111 177 117.1 171 85 177.1 61.3 77
#> 13.08 15.59 21.19 18.02 21.19 17.45 12.53 17.46 16.57 16.44 12.53 10.12 7.27
#> 149 6.1 125 36.1 6.2 197 108.1 154 107.2 86 68 79.2 5.1
#> 8.37 15.64 15.65 21.19 15.64 21.60 18.29 12.63 11.18 23.81 20.62 16.23 16.43
#> 81 180 155.1 158 41.2 76.1 8 41.3 14 43 175.1 92 187
#> 14.06 14.82 13.08 20.14 18.02 19.22 18.43 18.02 12.89 12.10 21.91 22.92 9.92
#> 24 107.3 123 190.1 60.1 69 92.1 145 25.1 16.1 63 183.2 173
#> 23.89 11.18 13.00 20.81 13.15 23.23 22.92 10.07 6.32 8.71 22.77 9.24 24.00
#> 142 67 161 148 22 35 62 193 53 131 173.1 118 131.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 2 82 116 1 118.1 186 119 65 102 148.1 173.2 83 47
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 82.1 161.1 112 143 3 7 82.2 72 116.1 126 172 53.1 148.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 48 44 161.2 17 151 22.1 11 87 2.1 12 80 144 1.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94 64 191 33 21 119.1 147 178 135 87.1 196 174 87.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 22.2 22.3 94.1 112.1 196.1 193.1 82.3 165 27 146 104 141 186.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 173.3 34 156 3.1 186.2 186.3 120 118.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[97]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.001824399 0.311959198 0.212490476
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.67288820 0.01322615 -0.36862452
#> grade_iii, Cure model
#> 1.00242650
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 58 19.34 1 39 0 0
#> 181 16.46 1 45 0 1
#> 70 7.38 1 30 1 0
#> 93 10.33 1 52 0 1
#> 184 17.77 1 38 0 0
#> 133 14.65 1 57 0 0
#> 199 19.81 1 NA 0 1
#> 15 22.68 1 48 0 0
#> 26 15.77 1 49 0 1
#> 89 11.44 1 NA 0 0
#> 175 21.91 1 43 0 0
#> 37 12.52 1 57 1 0
#> 166 19.98 1 48 0 0
#> 108 18.29 1 39 0 1
#> 153 21.33 1 55 1 0
#> 149 8.37 1 33 1 0
#> 101 9.97 1 10 0 1
#> 166.1 19.98 1 48 0 0
#> 199.1 19.81 1 NA 0 1
#> 150 20.33 1 48 0 0
#> 43 12.10 1 61 0 1
#> 149.1 8.37 1 33 1 0
#> 56 12.21 1 60 0 0
#> 129 23.41 1 53 1 0
#> 169 22.41 1 46 0 0
#> 25 6.32 1 34 1 0
#> 117 17.46 1 26 0 1
#> 140 12.68 1 59 1 0
#> 199.2 19.81 1 NA 0 1
#> 52 10.42 1 52 0 1
#> 180 14.82 1 37 0 0
#> 86 23.81 1 58 0 1
#> 189 10.51 1 NA 1 0
#> 8 18.43 1 32 0 0
#> 187 9.92 1 39 1 0
#> 85 16.44 1 36 0 0
#> 179 18.63 1 42 0 0
#> 170 19.54 1 43 0 1
#> 124 9.73 1 NA 1 0
#> 36 21.19 1 48 0 1
#> 97 19.14 1 65 0 1
#> 55 19.34 1 69 0 1
#> 69 23.23 1 25 0 1
#> 114 13.68 1 NA 0 0
#> 85.1 16.44 1 36 0 0
#> 81 14.06 1 34 0 0
#> 13 14.34 1 54 0 1
#> 177 12.53 1 75 0 0
#> 76 19.22 1 54 0 1
#> 92 22.92 1 47 0 1
#> 100 16.07 1 60 0 0
#> 91 5.33 1 61 0 1
#> 91.1 5.33 1 61 0 1
#> 189.1 10.51 1 NA 1 0
#> 42 12.43 1 49 0 1
#> 189.2 10.51 1 NA 1 0
#> 26.1 15.77 1 49 0 1
#> 29 15.45 1 68 1 0
#> 168 23.72 1 70 0 0
#> 39 15.59 1 37 0 1
#> 107 11.18 1 54 1 0
#> 26.2 15.77 1 49 0 1
#> 168.1 23.72 1 70 0 0
#> 130 16.47 1 53 0 1
#> 13.1 14.34 1 54 0 1
#> 190 20.81 1 42 1 0
#> 91.2 5.33 1 61 0 1
#> 130.1 16.47 1 53 0 1
#> 171 16.57 1 41 0 1
#> 100.1 16.07 1 60 0 0
#> 61 10.12 1 36 0 1
#> 113 22.86 1 34 0 0
#> 6 15.64 1 39 0 0
#> 37.1 12.52 1 57 1 0
#> 69.1 23.23 1 25 0 1
#> 113.1 22.86 1 34 0 0
#> 188 16.16 1 46 0 1
#> 92.1 22.92 1 47 0 1
#> 30 17.43 1 78 0 0
#> 76.1 19.22 1 54 0 1
#> 5 16.43 1 51 0 1
#> 153.1 21.33 1 55 1 0
#> 81.1 14.06 1 34 0 0
#> 81.2 14.06 1 34 0 0
#> 63 22.77 1 31 1 0
#> 60 13.15 1 38 1 0
#> 77 7.27 1 67 0 1
#> 180.1 14.82 1 37 0 0
#> 188.1 16.16 1 46 0 1
#> 6.1 15.64 1 39 0 0
#> 166.2 19.98 1 48 0 0
#> 15.1 22.68 1 48 0 0
#> 133.1 14.65 1 57 0 0
#> 57 14.46 1 45 0 1
#> 16 8.71 1 71 0 1
#> 40 18.00 1 28 1 0
#> 26.3 15.77 1 49 0 1
#> 136 21.83 1 43 0 1
#> 134 17.81 1 47 1 0
#> 51 18.23 1 83 0 1
#> 195 11.76 1 NA 1 0
#> 171.1 16.57 1 41 0 1
#> 101.1 9.97 1 10 0 1
#> 68 20.62 1 44 0 0
#> 133.2 14.65 1 57 0 0
#> 99 21.19 1 38 0 1
#> 85.2 16.44 1 36 0 0
#> 189.3 10.51 1 NA 1 0
#> 96 14.54 1 33 0 1
#> 55.1 19.34 1 69 0 1
#> 190.1 20.81 1 42 1 0
#> 100.2 16.07 1 60 0 0
#> 44 24.00 0 56 0 0
#> 146 24.00 0 63 1 0
#> 2 24.00 0 9 0 0
#> 172 24.00 0 41 0 0
#> 160 24.00 0 31 1 0
#> 7 24.00 0 37 1 0
#> 95 24.00 0 68 0 1
#> 112 24.00 0 61 0 0
#> 165 24.00 0 47 0 0
#> 67 24.00 0 25 0 0
#> 7.1 24.00 0 37 1 0
#> 94 24.00 0 51 0 1
#> 198 24.00 0 66 0 1
#> 98 24.00 0 34 1 0
#> 165.1 24.00 0 47 0 0
#> 9 24.00 0 31 1 0
#> 193 24.00 0 45 0 1
#> 141 24.00 0 44 1 0
#> 7.2 24.00 0 37 1 0
#> 144 24.00 0 28 0 1
#> 131 24.00 0 66 0 0
#> 148 24.00 0 61 1 0
#> 178 24.00 0 52 1 0
#> 31 24.00 0 36 0 1
#> 11 24.00 0 42 0 1
#> 163 24.00 0 66 0 0
#> 35 24.00 0 51 0 0
#> 200 24.00 0 64 0 0
#> 84 24.00 0 39 0 1
#> 54 24.00 0 53 1 0
#> 146.1 24.00 0 63 1 0
#> 65 24.00 0 57 1 0
#> 44.1 24.00 0 56 0 0
#> 132 24.00 0 55 0 0
#> 34 24.00 0 36 0 0
#> 1 24.00 0 23 1 0
#> 84.1 24.00 0 39 0 1
#> 104 24.00 0 50 1 0
#> 196 24.00 0 19 0 0
#> 83 24.00 0 6 0 0
#> 115 24.00 0 NA 1 0
#> 156 24.00 0 50 1 0
#> 122 24.00 0 66 0 0
#> 196.1 24.00 0 19 0 0
#> 65.1 24.00 0 57 1 0
#> 1.1 24.00 0 23 1 0
#> 186 24.00 0 45 1 0
#> 72 24.00 0 40 0 1
#> 182 24.00 0 35 0 0
#> 73 24.00 0 NA 0 1
#> 38 24.00 0 31 1 0
#> 161 24.00 0 45 0 0
#> 172.1 24.00 0 41 0 0
#> 165.2 24.00 0 47 0 0
#> 46 24.00 0 71 0 0
#> 193.1 24.00 0 45 0 1
#> 44.2 24.00 0 56 0 0
#> 119 24.00 0 17 0 0
#> 98.1 24.00 0 34 1 0
#> 163.1 24.00 0 66 0 0
#> 44.3 24.00 0 56 0 0
#> 142 24.00 0 53 0 0
#> 196.2 24.00 0 19 0 0
#> 48 24.00 0 31 1 0
#> 185 24.00 0 44 1 0
#> 144.1 24.00 0 28 0 1
#> 1.2 24.00 0 23 1 0
#> 147 24.00 0 76 1 0
#> 122.1 24.00 0 66 0 0
#> 172.2 24.00 0 41 0 0
#> 47 24.00 0 38 0 1
#> 46.1 24.00 0 71 0 0
#> 82 24.00 0 34 0 0
#> 94.1 24.00 0 51 0 1
#> 173 24.00 0 19 0 1
#> 160.1 24.00 0 31 1 0
#> 34.1 24.00 0 36 0 0
#> 87 24.00 0 27 0 0
#> 62 24.00 0 71 0 0
#> 132.1 24.00 0 55 0 0
#> 141.1 24.00 0 44 1 0
#> 22 24.00 0 52 1 0
#> 53 24.00 0 32 0 1
#> 19 24.00 0 57 0 1
#> 84.2 24.00 0 39 0 1
#> 132.2 24.00 0 55 0 0
#> 98.2 24.00 0 34 1 0
#> 178.1 24.00 0 52 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.673 NA NA NA
#> 2 age, Cure model 0.0132 NA NA NA
#> 3 grade_ii, Cure model -0.369 NA NA NA
#> 4 grade_iii, Cure model 1.00 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00182 NA NA NA
#> 2 grade_ii, Survival model 0.312 NA NA NA
#> 3 grade_iii, Survival model 0.212 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.67289 0.01323 -0.36862 1.00243
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 258
#> Residual Deviance: 242.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.67288820 0.01322615 -0.36862452 1.00242650
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.001824399 0.311959198 0.212490476
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.306410088 0.492668802 0.945337037 0.871221227 0.424816621 0.682477169
#> [7] 0.132928460 0.588067307 0.164587517 0.805460708 0.266792918 0.385278281
#> [13] 0.186292812 0.926993546 0.889931397 0.266792918 0.256674932 0.843044516
#> [19] 0.926993546 0.833620382 0.046389133 0.153741299 0.963709471 0.434632125
#> [25] 0.786515593 0.861845709 0.663526874 0.009412715 0.375291994 0.908444750
#> [31] 0.502327697 0.365320769 0.296284064 0.206735733 0.355369593 0.306410088
#> [37] 0.059157159 0.502327697 0.748803527 0.729912620 0.795980942 0.335692460
#> [43] 0.080561440 0.559574319 0.972866741 0.972866741 0.824207283 0.588067307
#> [49] 0.654000995 0.023124180 0.644446352 0.852457445 0.588067307 0.023124180
#> [55] 0.473488538 0.729912620 0.226894467 0.972866741 0.473488538 0.454212531
#> [61] 0.559574319 0.880584170 0.101259240 0.625435081 0.805460708 0.059157159
#> [67] 0.101259240 0.540515725 0.080561440 0.444408021 0.335692460 0.530853790
#> [73] 0.186292812 0.748803527 0.748803527 0.122229259 0.777024353 0.954527429
#> [79] 0.663526874 0.540515725 0.625435081 0.266792918 0.132928460 0.682477169
#> [85] 0.720375268 0.917723201 0.405156878 0.588067307 0.175488176 0.415016293
#> [91] 0.395225442 0.454212531 0.889931397 0.246590324 0.682477169 0.206735733
#> [97] 0.502327697 0.710820300 0.306410088 0.226894467 0.559574319 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000
#>
#> $Time
#> 58 181 70 93 184 133 15 26 175 37 166 108 153
#> 19.34 16.46 7.38 10.33 17.77 14.65 22.68 15.77 21.91 12.52 19.98 18.29 21.33
#> 149 101 166.1 150 43 149.1 56 129 169 25 117 140 52
#> 8.37 9.97 19.98 20.33 12.10 8.37 12.21 23.41 22.41 6.32 17.46 12.68 10.42
#> 180 86 8 187 85 179 170 36 97 55 69 85.1 81
#> 14.82 23.81 18.43 9.92 16.44 18.63 19.54 21.19 19.14 19.34 23.23 16.44 14.06
#> 13 177 76 92 100 91 91.1 42 26.1 29 168 39 107
#> 14.34 12.53 19.22 22.92 16.07 5.33 5.33 12.43 15.77 15.45 23.72 15.59 11.18
#> 26.2 168.1 130 13.1 190 91.2 130.1 171 100.1 61 113 6 37.1
#> 15.77 23.72 16.47 14.34 20.81 5.33 16.47 16.57 16.07 10.12 22.86 15.64 12.52
#> 69.1 113.1 188 92.1 30 76.1 5 153.1 81.1 81.2 63 60 77
#> 23.23 22.86 16.16 22.92 17.43 19.22 16.43 21.33 14.06 14.06 22.77 13.15 7.27
#> 180.1 188.1 6.1 166.2 15.1 133.1 57 16 40 26.3 136 134 51
#> 14.82 16.16 15.64 19.98 22.68 14.65 14.46 8.71 18.00 15.77 21.83 17.81 18.23
#> 171.1 101.1 68 133.2 99 85.2 96 55.1 190.1 100.2 44 146 2
#> 16.57 9.97 20.62 14.65 21.19 16.44 14.54 19.34 20.81 16.07 24.00 24.00 24.00
#> 172 160 7 95 112 165 67 7.1 94 198 98 165.1 9
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193 141 7.2 144 131 148 178 31 11 163 35 200 84
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 54 146.1 65 44.1 132 34 1 84.1 104 196 83 156 122
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 196.1 65.1 1.1 186 72 182 38 161 172.1 165.2 46 193.1 44.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 119 98.1 163.1 44.3 142 196.2 48 185 144.1 1.2 147 122.1 172.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 47 46.1 82 94.1 173 160.1 34.1 87 62 132.1 141.1 22 53
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 19 84.2 132.2 98.2 178.1
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[98]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.002958987 0.436319132 0.362171017
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.1752386 0.0197725 0.3019466
#> grade_iii, Cure model
#> 0.9465182
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 183 9.24 1 67 1 0
#> 86 23.81 1 58 0 1
#> 79 16.23 1 54 1 0
#> 124 9.73 1 NA 1 0
#> 52 10.42 1 52 0 1
#> 129 23.41 1 53 1 0
#> 194 22.40 1 38 0 1
#> 170 19.54 1 43 0 1
#> 113 22.86 1 34 0 0
#> 51 18.23 1 83 0 1
#> 89 11.44 1 NA 0 0
#> 108 18.29 1 39 0 1
#> 57 14.46 1 45 0 1
#> 59 10.16 1 NA 1 0
#> 36 21.19 1 48 0 1
#> 105 19.75 1 60 0 0
#> 100 16.07 1 60 0 0
#> 171 16.57 1 41 0 1
#> 93 10.33 1 52 0 1
#> 100.1 16.07 1 60 0 0
#> 78 23.88 1 43 0 0
#> 79.1 16.23 1 54 1 0
#> 97 19.14 1 65 0 1
#> 32 20.90 1 37 1 0
#> 97.1 19.14 1 65 0 1
#> 63 22.77 1 31 1 0
#> 66 22.13 1 53 0 0
#> 129.1 23.41 1 53 1 0
#> 164 23.60 1 76 0 1
#> 166 19.98 1 48 0 0
#> 199 19.81 1 NA 0 1
#> 164.1 23.60 1 76 0 1
#> 57.1 14.46 1 45 0 1
#> 136 21.83 1 43 0 1
#> 171.1 16.57 1 41 0 1
#> 42 12.43 1 49 0 1
#> 153 21.33 1 55 1 0
#> 140 12.68 1 59 1 0
#> 107 11.18 1 54 1 0
#> 106 16.67 1 49 1 0
#> 91 5.33 1 61 0 1
#> 177 12.53 1 75 0 0
#> 105.1 19.75 1 60 0 0
#> 5 16.43 1 51 0 1
#> 140.1 12.68 1 59 1 0
#> 14 12.89 1 21 0 0
#> 61 10.12 1 36 0 1
#> 42.1 12.43 1 49 0 1
#> 136.1 21.83 1 43 0 1
#> 29 15.45 1 68 1 0
#> 164.2 23.60 1 76 0 1
#> 158 20.14 1 74 1 0
#> 189 10.51 1 NA 1 0
#> 92 22.92 1 47 0 1
#> 167 15.55 1 56 1 0
#> 6 15.64 1 39 0 0
#> 129.2 23.41 1 53 1 0
#> 76 19.22 1 54 0 1
#> 150 20.33 1 48 0 0
#> 100.2 16.07 1 60 0 0
#> 179 18.63 1 42 0 0
#> 125 15.65 1 67 1 0
#> 79.2 16.23 1 54 1 0
#> 130 16.47 1 53 0 1
#> 78.1 23.88 1 43 0 0
#> 153.1 21.33 1 55 1 0
#> 197 21.60 1 69 1 0
#> 157 15.10 1 47 0 0
#> 79.3 16.23 1 54 1 0
#> 139 21.49 1 63 1 0
#> 91.1 5.33 1 61 0 1
#> 36.1 21.19 1 48 0 1
#> 69 23.23 1 25 0 1
#> 167.1 15.55 1 56 1 0
#> 157.1 15.10 1 47 0 0
#> 105.2 19.75 1 60 0 0
#> 153.2 21.33 1 55 1 0
#> 70 7.38 1 30 1 0
#> 175 21.91 1 43 0 0
#> 86.1 23.81 1 58 0 1
#> 4 17.64 1 NA 0 1
#> 129.3 23.41 1 53 1 0
#> 5.1 16.43 1 51 0 1
#> 153.3 21.33 1 55 1 0
#> 52.1 10.42 1 52 0 1
#> 79.4 16.23 1 54 1 0
#> 13 14.34 1 54 0 1
#> 13.1 14.34 1 54 0 1
#> 164.3 23.60 1 76 0 1
#> 52.2 10.42 1 52 0 1
#> 43 12.10 1 61 0 1
#> 180 14.82 1 37 0 0
#> 56 12.21 1 60 0 0
#> 93.1 10.33 1 52 0 1
#> 96 14.54 1 33 0 1
#> 157.2 15.10 1 47 0 0
#> 175.1 21.91 1 43 0 0
#> 183.1 9.24 1 67 1 0
#> 14.1 12.89 1 21 0 0
#> 78.2 23.88 1 43 0 0
#> 123 13.00 1 44 1 0
#> 136.2 21.83 1 43 0 1
#> 157.3 15.10 1 47 0 0
#> 24 23.89 1 38 0 0
#> 78.3 23.88 1 43 0 0
#> 123.1 13.00 1 44 1 0
#> 181 16.46 1 45 0 1
#> 6.1 15.64 1 39 0 0
#> 4.1 17.64 1 NA 0 1
#> 30 17.43 1 78 0 0
#> 169 22.41 1 46 0 0
#> 139.1 21.49 1 63 1 0
#> 35 24.00 0 51 0 0
#> 74 24.00 0 43 0 1
#> 122 24.00 0 66 0 0
#> 12 24.00 0 63 0 0
#> 48 24.00 0 31 1 0
#> 138 24.00 0 44 1 0
#> 121 24.00 0 57 1 0
#> 12.1 24.00 0 63 0 0
#> 53 24.00 0 32 0 1
#> 20 24.00 0 46 1 0
#> 163 24.00 0 66 0 0
#> 191 24.00 0 60 0 1
#> 83 24.00 0 6 0 0
#> 160 24.00 0 31 1 0
#> 21 24.00 0 47 0 0
#> 12.2 24.00 0 63 0 0
#> 115 24.00 0 NA 1 0
#> 138.1 24.00 0 44 1 0
#> 35.1 24.00 0 51 0 0
#> 48.1 24.00 0 31 1 0
#> 87 24.00 0 27 0 0
#> 87.1 24.00 0 27 0 0
#> 152 24.00 0 36 0 1
#> 74.1 24.00 0 43 0 1
#> 146 24.00 0 63 1 0
#> 121.1 24.00 0 57 1 0
#> 44 24.00 0 56 0 0
#> 122.1 24.00 0 66 0 0
#> 22 24.00 0 52 1 0
#> 109 24.00 0 48 0 0
#> 178 24.00 0 52 1 0
#> 131 24.00 0 66 0 0
#> 71 24.00 0 51 0 0
#> 109.1 24.00 0 48 0 0
#> 35.2 24.00 0 51 0 0
#> 19 24.00 0 57 0 1
#> 103 24.00 0 56 1 0
#> 172 24.00 0 41 0 0
#> 71.1 24.00 0 51 0 0
#> 196 24.00 0 19 0 0
#> 54 24.00 0 53 1 0
#> 54.1 24.00 0 53 1 0
#> 116 24.00 0 58 0 1
#> 62 24.00 0 71 0 0
#> 46 24.00 0 71 0 0
#> 109.2 24.00 0 48 0 0
#> 3 24.00 0 31 1 0
#> 104 24.00 0 50 1 0
#> 80 24.00 0 41 0 0
#> 65 24.00 0 57 1 0
#> 156 24.00 0 50 1 0
#> 103.1 24.00 0 56 1 0
#> 115.1 24.00 0 NA 1 0
#> 87.2 24.00 0 27 0 0
#> 53.1 24.00 0 32 0 1
#> 185 24.00 0 44 1 0
#> 67 24.00 0 25 0 0
#> 165 24.00 0 47 0 0
#> 146.1 24.00 0 63 1 0
#> 198 24.00 0 66 0 1
#> 176 24.00 0 43 0 1
#> 163.1 24.00 0 66 0 0
#> 152.1 24.00 0 36 0 1
#> 28 24.00 0 67 1 0
#> 152.2 24.00 0 36 0 1
#> 33 24.00 0 53 0 0
#> 165.1 24.00 0 47 0 0
#> 173 24.00 0 19 0 1
#> 198.1 24.00 0 66 0 1
#> 7 24.00 0 37 1 0
#> 142 24.00 0 53 0 0
#> 11 24.00 0 42 0 1
#> 20.1 24.00 0 46 1 0
#> 120 24.00 0 68 0 1
#> 87.3 24.00 0 27 0 0
#> 193 24.00 0 45 0 1
#> 27 24.00 0 63 1 0
#> 44.1 24.00 0 56 0 0
#> 115.2 24.00 0 NA 1 0
#> 148 24.00 0 61 1 0
#> 102 24.00 0 49 0 0
#> 200 24.00 0 64 0 0
#> 35.3 24.00 0 51 0 0
#> 31 24.00 0 36 0 1
#> 53.2 24.00 0 32 0 1
#> 17 24.00 0 38 0 1
#> 131.1 24.00 0 66 0 0
#> 27.1 24.00 0 63 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.18 NA NA NA
#> 2 age, Cure model 0.0198 NA NA NA
#> 3 grade_ii, Cure model 0.302 NA NA NA
#> 4 grade_iii, Cure model 0.947 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00296 NA NA NA
#> 2 grade_ii, Survival model 0.436 NA NA NA
#> 3 grade_iii, Survival model 0.362 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.17524 0.01977 0.30195 0.94652
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 261.3
#> Residual Deviance: 251.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.1752386 0.0197725 0.3019466 0.9465182
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.002958987 0.436319132 0.362171017
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.95875434 0.07811429 0.59992918 0.90876916 0.14854578 0.24169500
#> [7] 0.46279058 0.21006965 0.51833111 0.50910176 0.77252544 0.37918718
#> [13] 0.43510769 0.64245493 0.54597136 0.93374950 0.64245493 0.03157371
#> [19] 0.59992918 0.48148411 0.39778905 0.48148411 0.22072961 0.25207992
#> [25] 0.14854578 0.10466447 0.42577604 0.10466447 0.77252544 0.28319990
#> [31] 0.54597136 0.86643439 0.34246399 0.84096809 0.90031056 0.53678253
#> [37] 0.98357157 0.85790625 0.43510769 0.58213264 0.84096809 0.82392726
#> [43] 0.95040911 0.86643439 0.28319990 0.71203764 0.10466447 0.41647140
#> [49] 0.19946132 0.69471250 0.67725208 0.14854578 0.47215809 0.40711603
#> [55] 0.64245493 0.49982535 0.66848965 0.59992918 0.56403030 0.03157371
#> [61] 0.34246399 0.31279714 0.72072536 0.59992918 0.32290547 0.98357157
#> [67] 0.37918718 0.18871025 0.69471250 0.72072536 0.43510769 0.34246399
#> [73] 0.97529511 0.26252737 0.07811429 0.14854578 0.58213264 0.34246399
#> [79] 0.90876916 0.59992918 0.78975851 0.78975851 0.10466447 0.90876916
#> [85] 0.89182657 0.75506435 0.88332647 0.93374950 0.76381000 0.72072536
#> [91] 0.26252737 0.95875434 0.82392726 0.03157371 0.80690765 0.28319990
#> [97] 0.72072536 0.01031210 0.03157371 0.80690765 0.57309986 0.67725208
#> [103] 0.52754019 0.23118202 0.32290547 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 183 86 79 52 129 194 170 113 51 108 57 36 105
#> 9.24 23.81 16.23 10.42 23.41 22.40 19.54 22.86 18.23 18.29 14.46 21.19 19.75
#> 100 171 93 100.1 78 79.1 97 32 97.1 63 66 129.1 164
#> 16.07 16.57 10.33 16.07 23.88 16.23 19.14 20.90 19.14 22.77 22.13 23.41 23.60
#> 166 164.1 57.1 136 171.1 42 153 140 107 106 91 177 105.1
#> 19.98 23.60 14.46 21.83 16.57 12.43 21.33 12.68 11.18 16.67 5.33 12.53 19.75
#> 5 140.1 14 61 42.1 136.1 29 164.2 158 92 167 6 129.2
#> 16.43 12.68 12.89 10.12 12.43 21.83 15.45 23.60 20.14 22.92 15.55 15.64 23.41
#> 76 150 100.2 179 125 79.2 130 78.1 153.1 197 157 79.3 139
#> 19.22 20.33 16.07 18.63 15.65 16.23 16.47 23.88 21.33 21.60 15.10 16.23 21.49
#> 91.1 36.1 69 167.1 157.1 105.2 153.2 70 175 86.1 129.3 5.1 153.3
#> 5.33 21.19 23.23 15.55 15.10 19.75 21.33 7.38 21.91 23.81 23.41 16.43 21.33
#> 52.1 79.4 13 13.1 164.3 52.2 43 180 56 93.1 96 157.2 175.1
#> 10.42 16.23 14.34 14.34 23.60 10.42 12.10 14.82 12.21 10.33 14.54 15.10 21.91
#> 183.1 14.1 78.2 123 136.2 157.3 24 78.3 123.1 181 6.1 30 169
#> 9.24 12.89 23.88 13.00 21.83 15.10 23.89 23.88 13.00 16.46 15.64 17.43 22.41
#> 139.1 35 74 122 12 48 138 121 12.1 53 20 163 191
#> 21.49 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 83 160 21 12.2 138.1 35.1 48.1 87 87.1 152 74.1 146 121.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44 122.1 22 109 178 131 71 109.1 35.2 19 103 172 71.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 196 54 54.1 116 62 46 109.2 3 104 80 65 156 103.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87.2 53.1 185 67 165 146.1 198 176 163.1 152.1 28 152.2 33
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165.1 173 198.1 7 142 11 20.1 120 87.3 193 27 44.1 148
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 102 200 35.3 31 53.2 17 131.1 27.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[99]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.004672863 0.798796287 0.332804213
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.81681078 0.01862399 -0.22874732
#> grade_iii, Cure model
#> 0.41339196
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 117 17.46 1 26 0 1
#> 4 17.64 1 NA 0 1
#> 68 20.62 1 44 0 0
#> 158 20.14 1 74 1 0
#> 155 13.08 1 26 0 0
#> 183 9.24 1 67 1 0
#> 110 17.56 1 65 0 1
#> 56 12.21 1 60 0 0
#> 86 23.81 1 58 0 1
#> 32 20.90 1 37 1 0
#> 96 14.54 1 33 0 1
#> 41 18.02 1 40 1 0
#> 63 22.77 1 31 1 0
#> 184 17.77 1 38 0 0
#> 55 19.34 1 69 0 1
#> 96.1 14.54 1 33 0 1
#> 136 21.83 1 43 0 1
#> 189 10.51 1 NA 1 0
#> 89 11.44 1 NA 0 0
#> 45 17.42 1 54 0 1
#> 5 16.43 1 51 0 1
#> 195 11.76 1 NA 1 0
#> 50 10.02 1 NA 1 0
#> 105 19.75 1 60 0 0
#> 50.1 10.02 1 NA 1 0
#> 14 12.89 1 21 0 0
#> 68.1 20.62 1 44 0 0
#> 177 12.53 1 75 0 0
#> 123 13.00 1 44 1 0
#> 164 23.60 1 76 0 1
#> 199 19.81 1 NA 0 1
#> 117.1 17.46 1 26 0 1
#> 199.1 19.81 1 NA 0 1
#> 86.1 23.81 1 58 0 1
#> 24 23.89 1 38 0 0
#> 93 10.33 1 52 0 1
#> 91 5.33 1 61 0 1
#> 13 14.34 1 54 0 1
#> 105.1 19.75 1 60 0 0
#> 49 12.19 1 48 1 0
#> 124 9.73 1 NA 1 0
#> 169 22.41 1 46 0 0
#> 168 23.72 1 70 0 0
#> 18 15.21 1 49 1 0
#> 16 8.71 1 71 0 1
#> 81 14.06 1 34 0 0
#> 169.1 22.41 1 46 0 0
#> 66 22.13 1 53 0 0
#> 90 20.94 1 50 0 1
#> 184.1 17.77 1 38 0 0
#> 117.2 17.46 1 26 0 1
#> 14.1 12.89 1 21 0 0
#> 68.2 20.62 1 44 0 0
#> 93.1 10.33 1 52 0 1
#> 59 10.16 1 NA 1 0
#> 70 7.38 1 30 1 0
#> 36 21.19 1 48 0 1
#> 37 12.52 1 57 1 0
#> 199.2 19.81 1 NA 0 1
#> 179 18.63 1 42 0 0
#> 110.1 17.56 1 65 0 1
#> 60 13.15 1 38 1 0
#> 81.1 14.06 1 34 0 0
#> 127 3.53 1 62 0 1
#> 70.1 7.38 1 30 1 0
#> 99 21.19 1 38 0 1
#> 113 22.86 1 34 0 0
#> 6 15.64 1 39 0 0
#> 180 14.82 1 37 0 0
#> 40 18.00 1 28 1 0
#> 188 16.16 1 46 0 1
#> 90.1 20.94 1 50 0 1
#> 168.1 23.72 1 70 0 0
#> 110.2 17.56 1 65 0 1
#> 107 11.18 1 54 1 0
#> 159 10.55 1 50 0 1
#> 184.2 17.77 1 38 0 0
#> 63.1 22.77 1 31 1 0
#> 195.1 11.76 1 NA 1 0
#> 78 23.88 1 43 0 0
#> 15 22.68 1 48 0 0
#> 194 22.40 1 38 0 1
#> 25 6.32 1 34 1 0
#> 130 16.47 1 53 0 1
#> 92 22.92 1 47 0 1
#> 111 17.45 1 47 0 1
#> 59.1 10.16 1 NA 1 0
#> 24.1 23.89 1 38 0 0
#> 32.1 20.90 1 37 1 0
#> 177.1 12.53 1 75 0 0
#> 93.2 10.33 1 52 0 1
#> 42 12.43 1 49 0 1
#> 55.1 19.34 1 69 0 1
#> 85 16.44 1 36 0 0
#> 183.1 9.24 1 67 1 0
#> 30 17.43 1 78 0 0
#> 158.1 20.14 1 74 1 0
#> 175 21.91 1 43 0 0
#> 150 20.33 1 48 0 0
#> 89.1 11.44 1 NA 0 0
#> 170 19.54 1 43 0 1
#> 199.3 19.81 1 NA 0 1
#> 41.1 18.02 1 40 1 0
#> 69 23.23 1 25 0 1
#> 128 20.35 1 35 0 1
#> 194.1 22.40 1 38 0 1
#> 29 15.45 1 68 1 0
#> 29.1 15.45 1 68 1 0
#> 125 15.65 1 67 1 0
#> 166 19.98 1 48 0 0
#> 79 16.23 1 54 1 0
#> 13.1 14.34 1 54 0 1
#> 19 24.00 0 57 0 1
#> 143 24.00 0 51 0 0
#> 38 24.00 0 31 1 0
#> 53 24.00 0 32 0 1
#> 172 24.00 0 41 0 0
#> 198 24.00 0 66 0 1
#> 11 24.00 0 42 0 1
#> 132 24.00 0 55 0 0
#> 144 24.00 0 28 0 1
#> 65 24.00 0 57 1 0
#> 82 24.00 0 34 0 0
#> 74 24.00 0 43 0 1
#> 144.1 24.00 0 28 0 1
#> 142 24.00 0 53 0 0
#> 44 24.00 0 56 0 0
#> 7 24.00 0 37 1 0
#> 12 24.00 0 63 0 0
#> 17 24.00 0 38 0 1
#> 147 24.00 0 76 1 0
#> 53.1 24.00 0 32 0 1
#> 178 24.00 0 52 1 0
#> 38.1 24.00 0 31 1 0
#> 84 24.00 0 39 0 1
#> 73 24.00 0 NA 0 1
#> 35 24.00 0 51 0 0
#> 98 24.00 0 34 1 0
#> 173 24.00 0 19 0 1
#> 67 24.00 0 25 0 0
#> 95 24.00 0 68 0 1
#> 80 24.00 0 41 0 0
#> 161 24.00 0 45 0 0
#> 196 24.00 0 19 0 0
#> 173.1 24.00 0 19 0 1
#> 54 24.00 0 53 1 0
#> 185 24.00 0 44 1 0
#> 28 24.00 0 67 1 0
#> 174 24.00 0 49 1 0
#> 31 24.00 0 36 0 1
#> 186 24.00 0 45 1 0
#> 162 24.00 0 51 0 0
#> 19.1 24.00 0 57 0 1
#> 122 24.00 0 66 0 0
#> 121 24.00 0 57 1 0
#> 173.2 24.00 0 19 0 1
#> 200 24.00 0 64 0 0
#> 160 24.00 0 31 1 0
#> 12.1 24.00 0 63 0 0
#> 84.1 24.00 0 39 0 1
#> 135 24.00 0 58 1 0
#> 11.1 24.00 0 42 0 1
#> 174.1 24.00 0 49 1 0
#> 122.1 24.00 0 66 0 0
#> 151 24.00 0 42 0 0
#> 84.2 24.00 0 39 0 1
#> 19.2 24.00 0 57 0 1
#> 196.1 24.00 0 19 0 0
#> 20 24.00 0 46 1 0
#> 7.1 24.00 0 37 1 0
#> 33 24.00 0 53 0 0
#> 119 24.00 0 17 0 0
#> 172.1 24.00 0 41 0 0
#> 126 24.00 0 48 0 0
#> 144.2 24.00 0 28 0 1
#> 121.1 24.00 0 57 1 0
#> 67.1 24.00 0 25 0 0
#> 19.3 24.00 0 57 0 1
#> 2 24.00 0 9 0 0
#> 102 24.00 0 49 0 0
#> 138 24.00 0 44 1 0
#> 163 24.00 0 66 0 0
#> 9 24.00 0 31 1 0
#> 47 24.00 0 38 0 1
#> 147.1 24.00 0 76 1 0
#> 132.1 24.00 0 55 0 0
#> 73.1 24.00 0 NA 0 1
#> 141 24.00 0 44 1 0
#> 174.2 24.00 0 49 1 0
#> 2.1 24.00 0 9 0 0
#> 1 24.00 0 23 1 0
#> 80.1 24.00 0 41 0 0
#> 122.2 24.00 0 66 0 0
#> 173.3 24.00 0 19 0 1
#> 120 24.00 0 68 0 1
#> 35.1 24.00 0 51 0 0
#> 141.1 24.00 0 44 1 0
#> 7.2 24.00 0 37 1 0
#> 64 24.00 0 43 0 0
#> 121.2 24.00 0 57 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.817 NA NA NA
#> 2 age, Cure model 0.0186 NA NA NA
#> 3 grade_ii, Cure model -0.229 NA NA NA
#> 4 grade_iii, Cure model 0.413 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00467 NA NA NA
#> 2 grade_ii, Survival model 0.799 NA NA NA
#> 3 grade_iii, Survival model 0.333 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.81681 0.01862 -0.22875 0.41339
#>
#> Degrees of Freedom: 182 Total (i.e. Null); 179 Residual
#> Null Deviance: 253
#> Residual Deviance: 246.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.81681078 0.01862399 -0.22874732 0.41339196
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.004672863 0.798796287 0.332804213
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.6886492 0.4820652 0.5330799 0.8605399 0.9542729 0.6649921 0.9117265
#> [8] 0.1331693 0.4611732 0.8141487 0.6153987 0.2838037 0.6405617 0.5887847
#> [15] 0.8141487 0.4026911 0.7273230 0.7501480 0.5611730 0.8735284 0.4820652
#> [22] 0.8863657 0.8670763 0.2139807 0.6886492 0.1331693 0.0437022 0.9363974
#> [29] 0.9887752 0.8275572 0.5611730 0.9179965 0.3251652 0.1753436 0.8005326
#> [36] 0.9659294 0.8407951 0.3251652 0.3772066 0.4386024 0.6405617 0.6886492
#> [43] 0.8735284 0.4820652 0.9363974 0.9717422 0.4151109 0.8991253 0.6065025
#> [50] 0.6649921 0.8539972 0.8407951 0.9944013 0.9717422 0.4151109 0.2671244
#> [57] 0.7795749 0.8073460 0.6322501 0.7650509 0.4386024 0.1753436 0.6649921
#> [64] 0.9241912 0.9303096 0.6405617 0.2838037 0.1009577 0.3112717 0.3518256
#> [71] 0.9831216 0.7349776 0.2502643 0.7118482 0.0437022 0.4611732 0.8863657
#> [78] 0.9363974 0.9054424 0.5887847 0.7425699 0.9542729 0.7196039 0.5330799
#> [85] 0.3899952 0.5228719 0.5796004 0.6153987 0.2325235 0.5126135 0.3518256
#> [92] 0.7867540 0.7867540 0.7723825 0.5517818 0.7576676 0.8275572 0.0000000
#> [99] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [106] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [183] 0.0000000
#>
#> $Time
#> 117 68 158 155 183 110 56 86 32 96 41 63 184
#> 17.46 20.62 20.14 13.08 9.24 17.56 12.21 23.81 20.90 14.54 18.02 22.77 17.77
#> 55 96.1 136 45 5 105 14 68.1 177 123 164 117.1 86.1
#> 19.34 14.54 21.83 17.42 16.43 19.75 12.89 20.62 12.53 13.00 23.60 17.46 23.81
#> 24 93 91 13 105.1 49 169 168 18 16 81 169.1 66
#> 23.89 10.33 5.33 14.34 19.75 12.19 22.41 23.72 15.21 8.71 14.06 22.41 22.13
#> 90 184.1 117.2 14.1 68.2 93.1 70 36 37 179 110.1 60 81.1
#> 20.94 17.77 17.46 12.89 20.62 10.33 7.38 21.19 12.52 18.63 17.56 13.15 14.06
#> 127 70.1 99 113 6 180 40 188 90.1 168.1 110.2 107 159
#> 3.53 7.38 21.19 22.86 15.64 14.82 18.00 16.16 20.94 23.72 17.56 11.18 10.55
#> 184.2 63.1 78 15 194 25 130 92 111 24.1 32.1 177.1 93.2
#> 17.77 22.77 23.88 22.68 22.40 6.32 16.47 22.92 17.45 23.89 20.90 12.53 10.33
#> 42 55.1 85 183.1 30 158.1 175 150 170 41.1 69 128 194.1
#> 12.43 19.34 16.44 9.24 17.43 20.14 21.91 20.33 19.54 18.02 23.23 20.35 22.40
#> 29 29.1 125 166 79 13.1 19 143 38 53 172 198 11
#> 15.45 15.45 15.65 19.98 16.23 14.34 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 132 144 65 82 74 144.1 142 44 7 12 17 147 53.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178 38.1 84 35 98 173 67 95 80 161 196 173.1 54
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185 28 174 31 186 162 19.1 122 121 173.2 200 160 12.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 84.1 135 11.1 174.1 122.1 151 84.2 19.2 196.1 20 7.1 33 119
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172.1 126 144.2 121.1 67.1 19.3 2 102 138 163 9 47 147.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 132.1 141 174.2 2.1 1 80.1 122.2 173.3 120 35.1 141.1 7.2 64
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 121.2
#> 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[100]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01042355 1.18963287 0.86339747
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.28442742 0.00601149 -0.38848874
#> grade_iii, Cure model
#> 1.35064152
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x56211437de80>
#>
#> $data
#> time status age grade_ii grade_iii
#> 61 10.12 1 36 0 1
#> 130 16.47 1 53 0 1
#> 190 20.81 1 42 1 0
#> 37 12.52 1 57 1 0
#> 66 22.13 1 53 0 0
#> 24 23.89 1 38 0 0
#> 58 19.34 1 39 0 0
#> 30 17.43 1 78 0 0
#> 167 15.55 1 56 1 0
#> 13 14.34 1 54 0 1
#> 97 19.14 1 65 0 1
#> 60 13.15 1 38 1 0
#> 164 23.60 1 76 0 1
#> 183 9.24 1 67 1 0
#> 15 22.68 1 48 0 0
#> 25 6.32 1 34 1 0
#> 100 16.07 1 60 0 0
#> 106 16.67 1 49 1 0
#> 107 11.18 1 54 1 0
#> 167.1 15.55 1 56 1 0
#> 184 17.77 1 38 0 0
#> 114 13.68 1 NA 0 0
#> 24.1 23.89 1 38 0 0
#> 4 17.64 1 NA 0 1
#> 175 21.91 1 43 0 0
#> 59 10.16 1 NA 1 0
#> 194 22.40 1 38 0 1
#> 99 21.19 1 38 0 1
#> 123 13.00 1 44 1 0
#> 93 10.33 1 52 0 1
#> 168 23.72 1 70 0 0
#> 90 20.94 1 50 0 1
#> 180 14.82 1 37 0 0
#> 59.1 10.16 1 NA 1 0
#> 96 14.54 1 33 0 1
#> 70 7.38 1 30 1 0
#> 111 17.45 1 47 0 1
#> 16 8.71 1 71 0 1
#> 197 21.60 1 69 1 0
#> 5 16.43 1 51 0 1
#> 26 15.77 1 49 0 1
#> 125 15.65 1 67 1 0
#> 39 15.59 1 37 0 1
#> 56 12.21 1 60 0 0
#> 59.2 10.16 1 NA 1 0
#> 134 17.81 1 47 1 0
#> 58.1 19.34 1 39 0 0
#> 81 14.06 1 34 0 0
#> 81.1 14.06 1 34 0 0
#> 88 18.37 1 47 0 0
#> 110 17.56 1 65 0 1
#> 57 14.46 1 45 0 1
#> 125.1 15.65 1 67 1 0
#> 91 5.33 1 61 0 1
#> 113 22.86 1 34 0 0
#> 24.2 23.89 1 38 0 0
#> 41 18.02 1 40 1 0
#> 85 16.44 1 36 0 0
#> 133 14.65 1 57 0 0
#> 50 10.02 1 NA 1 0
#> 52 10.42 1 52 0 1
#> 124 9.73 1 NA 1 0
#> 6 15.64 1 39 0 0
#> 140 12.68 1 59 1 0
#> 43 12.10 1 61 0 1
#> 181 16.46 1 45 0 1
#> 195 11.76 1 NA 1 0
#> 153 21.33 1 55 1 0
#> 187 9.92 1 39 1 0
#> 111.1 17.45 1 47 0 1
#> 76 19.22 1 54 0 1
#> 189 10.51 1 NA 1 0
#> 85.1 16.44 1 36 0 0
#> 16.1 8.71 1 71 0 1
#> 183.1 9.24 1 67 1 0
#> 79 16.23 1 54 1 0
#> 88.1 18.37 1 47 0 0
#> 110.1 17.56 1 65 0 1
#> 23 16.92 1 61 0 0
#> 70.1 7.38 1 30 1 0
#> 168.1 23.72 1 70 0 0
#> 105 19.75 1 60 0 0
#> 42 12.43 1 49 0 1
#> 107.1 11.18 1 54 1 0
#> 130.1 16.47 1 53 0 1
#> 90.1 20.94 1 50 0 1
#> 89 11.44 1 NA 0 0
#> 181.1 16.46 1 45 0 1
#> 16.2 8.71 1 71 0 1
#> 4.1 17.64 1 NA 0 1
#> 168.2 23.72 1 70 0 0
#> 25.1 6.32 1 34 1 0
#> 180.1 14.82 1 37 0 0
#> 14 12.89 1 21 0 0
#> 10 10.53 1 34 0 0
#> 85.2 16.44 1 36 0 0
#> 168.3 23.72 1 70 0 0
#> 36 21.19 1 48 0 1
#> 40 18.00 1 28 1 0
#> 25.2 6.32 1 34 1 0
#> 42.1 12.43 1 49 0 1
#> 68 20.62 1 44 0 0
#> 16.3 8.71 1 71 0 1
#> 51 18.23 1 83 0 1
#> 113.1 22.86 1 34 0 0
#> 197.1 21.60 1 69 1 0
#> 79.1 16.23 1 54 1 0
#> 36.1 21.19 1 48 0 1
#> 105.1 19.75 1 60 0 0
#> 117 17.46 1 26 0 1
#> 124.1 9.73 1 NA 1 0
#> 192 16.44 1 31 1 0
#> 141 24.00 0 44 1 0
#> 33 24.00 0 53 0 0
#> 138 24.00 0 44 1 0
#> 82 24.00 0 34 0 0
#> 48 24.00 0 31 1 0
#> 122 24.00 0 66 0 0
#> 141.1 24.00 0 44 1 0
#> 34 24.00 0 36 0 0
#> 22 24.00 0 52 1 0
#> 162 24.00 0 51 0 0
#> 21 24.00 0 47 0 0
#> 82.1 24.00 0 34 0 0
#> 98 24.00 0 34 1 0
#> 160 24.00 0 31 1 0
#> 64 24.00 0 43 0 0
#> 27 24.00 0 63 1 0
#> 148 24.00 0 61 1 0
#> 54 24.00 0 53 1 0
#> 122.1 24.00 0 66 0 0
#> 98.1 24.00 0 34 1 0
#> 148.1 24.00 0 61 1 0
#> 46 24.00 0 71 0 0
#> 196 24.00 0 19 0 0
#> 87 24.00 0 27 0 0
#> 186 24.00 0 45 1 0
#> 9 24.00 0 31 1 0
#> 19 24.00 0 57 0 1
#> 103 24.00 0 56 1 0
#> 156 24.00 0 50 1 0
#> 65 24.00 0 57 1 0
#> 119 24.00 0 17 0 0
#> 131 24.00 0 66 0 0
#> 146 24.00 0 63 1 0
#> 160.1 24.00 0 31 1 0
#> 54.1 24.00 0 53 1 0
#> 102 24.00 0 49 0 0
#> 112 24.00 0 61 0 0
#> 165 24.00 0 47 0 0
#> 112.1 24.00 0 61 0 0
#> 38 24.00 0 31 1 0
#> 94 24.00 0 51 0 1
#> 27.1 24.00 0 63 1 0
#> 7 24.00 0 37 1 0
#> 1 24.00 0 23 1 0
#> 191 24.00 0 60 0 1
#> 122.2 24.00 0 66 0 0
#> 178 24.00 0 52 1 0
#> 178.1 24.00 0 52 1 0
#> 1.1 24.00 0 23 1 0
#> 73 24.00 0 NA 0 1
#> 20 24.00 0 46 1 0
#> 67 24.00 0 25 0 0
#> 143 24.00 0 51 0 0
#> 67.1 24.00 0 25 0 0
#> 109 24.00 0 48 0 0
#> 27.2 24.00 0 63 1 0
#> 120 24.00 0 68 0 1
#> 126 24.00 0 48 0 0
#> 22.1 24.00 0 52 1 0
#> 62 24.00 0 71 0 0
#> 118 24.00 0 44 1 0
#> 142 24.00 0 53 0 0
#> 131.1 24.00 0 66 0 0
#> 160.2 24.00 0 31 1 0
#> 126.1 24.00 0 48 0 0
#> 160.3 24.00 0 31 1 0
#> 120.1 24.00 0 68 0 1
#> 151 24.00 0 42 0 0
#> 11 24.00 0 42 0 1
#> 143.1 24.00 0 51 0 0
#> 98.2 24.00 0 34 1 0
#> 46.1 24.00 0 71 0 0
#> 19.1 24.00 0 57 0 1
#> 148.2 24.00 0 61 1 0
#> 147 24.00 0 76 1 0
#> 44 24.00 0 56 0 0
#> 75 24.00 0 21 1 0
#> 75.1 24.00 0 21 1 0
#> 84 24.00 0 39 0 1
#> 7.1 24.00 0 37 1 0
#> 162.1 24.00 0 51 0 0
#> 3 24.00 0 31 1 0
#> 137 24.00 0 45 1 0
#> 137.1 24.00 0 45 1 0
#> 119.1 24.00 0 17 0 0
#> 19.2 24.00 0 57 0 1
#> 182 24.00 0 35 0 0
#> 22.2 24.00 0 52 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.284 NA NA NA
#> 2 age, Cure model 0.00601 NA NA NA
#> 3 grade_ii, Cure model -0.388 NA NA NA
#> 4 grade_iii, Cure model 1.35 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0104 NA NA NA
#> 2 grade_ii, Survival model 1.19 NA NA NA
#> 3 grade_iii, Survival model 0.863 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.284427 0.006011 -0.388489 1.350642
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 258.3
#> Residual Deviance: 238.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.28442742 0.00601149 -0.38848874 1.35064152
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01042355 1.18963287 0.86339747
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.887805500 0.512942006 0.260161449 0.802086266 0.132346694 0.005039799
#> [7] 0.304742462 0.481847375 0.675827573 0.739459457 0.339505198 0.766579867
#> [13] 0.061360630 0.904556886 0.102233579 0.969216292 0.619595082 0.502680969
#> [19] 0.845356887 0.675827573 0.419288426 0.005039799 0.147540201 0.117860101
#> [25] 0.203612233 0.775548487 0.879332723 0.022273036 0.237730057 0.693865144
#> [31] 0.721260341 0.953288800 0.461580443 0.920947974 0.163321723 0.590987143
#> [37] 0.629157229 0.638658323 0.666539947 0.828007583 0.408605847 0.304742462
#> [43] 0.748492765 0.748492765 0.351055411 0.430060778 0.730387299 0.638658323
#> [49] 0.992270414 0.074883541 0.005039799 0.386200719 0.552640082 0.712054044
#> [55] 0.870828890 0.657172388 0.793284759 0.836693725 0.532969637 0.190390208
#> [61] 0.896227697 0.461580443 0.327874206 0.552640082 0.920947974 0.904556886
#> [67] 0.600752519 0.351055411 0.430060778 0.492212309 0.953288800 0.022273036
#> [73] 0.282183248 0.810809861 0.845356887 0.512942006 0.237730057 0.532969637
#> [79] 0.920947974 0.022273036 0.969216292 0.693865144 0.784406767 0.862293467
#> [85] 0.552640082 0.022273036 0.203612233 0.397632632 0.969216292 0.810809861
#> [91] 0.271090075 0.920947974 0.374360341 0.074883541 0.163321723 0.600752519
#> [97] 0.203612233 0.282183248 0.451123076 0.552640082 0.000000000 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000
#>
#> $Time
#> 61 130 190 37 66 24 58 30 167 13 97 60 164
#> 10.12 16.47 20.81 12.52 22.13 23.89 19.34 17.43 15.55 14.34 19.14 13.15 23.60
#> 183 15 25 100 106 107 167.1 184 24.1 175 194 99 123
#> 9.24 22.68 6.32 16.07 16.67 11.18 15.55 17.77 23.89 21.91 22.40 21.19 13.00
#> 93 168 90 180 96 70 111 16 197 5 26 125 39
#> 10.33 23.72 20.94 14.82 14.54 7.38 17.45 8.71 21.60 16.43 15.77 15.65 15.59
#> 56 134 58.1 81 81.1 88 110 57 125.1 91 113 24.2 41
#> 12.21 17.81 19.34 14.06 14.06 18.37 17.56 14.46 15.65 5.33 22.86 23.89 18.02
#> 85 133 52 6 140 43 181 153 187 111.1 76 85.1 16.1
#> 16.44 14.65 10.42 15.64 12.68 12.10 16.46 21.33 9.92 17.45 19.22 16.44 8.71
#> 183.1 79 88.1 110.1 23 70.1 168.1 105 42 107.1 130.1 90.1 181.1
#> 9.24 16.23 18.37 17.56 16.92 7.38 23.72 19.75 12.43 11.18 16.47 20.94 16.46
#> 16.2 168.2 25.1 180.1 14 10 85.2 168.3 36 40 25.2 42.1 68
#> 8.71 23.72 6.32 14.82 12.89 10.53 16.44 23.72 21.19 18.00 6.32 12.43 20.62
#> 16.3 51 113.1 197.1 79.1 36.1 105.1 117 192 141 33 138 82
#> 8.71 18.23 22.86 21.60 16.23 21.19 19.75 17.46 16.44 24.00 24.00 24.00 24.00
#> 48 122 141.1 34 22 162 21 82.1 98 160 64 27 148
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 54 122.1 98.1 148.1 46 196 87 186 9 19 103 156 65
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 119 131 146 160.1 54.1 102 112 165 112.1 38 94 27.1 7
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1 191 122.2 178 178.1 1.1 20 67 143 67.1 109 27.2 120
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126 22.1 62 118 142 131.1 160.2 126.1 160.3 120.1 151 11 143.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98.2 46.1 19.1 148.2 147 44 75 75.1 84 7.1 162.1 3 137
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137.1 119.1 19.2 182 22.2
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> Formula blueprint:
#>
#> # Predictors: 2
#> # Outcomes: 2
#> Intercept: TRUE
#> Novel Levels: FALSE
#> Composition: tibble
#> Indicators: traditional
#>
#> $cure_blueprint
#> Formula blueprint:
#>
#> # Predictors: 2
#> # Outcomes: 0
#> Intercept: TRUE
#> Novel Levels: FALSE
#> Composition: tibble
#> Indicators: traditional
#>